Sometimes buzzwords like "artificial intelligence" or "neural network" can take on their own life. Just look at the explosion and success of ChatGPT, which we've used to generate inspiration for our blog "10 Reasons You Should Digitise Your Lab Operations." The blog below outlines the actionable steps to wielding the power of big data, machine learning, and more in the life sciences. 

Moving Beyond Buzzwords: A Few Definitions

But before we dive in, let's get some clear definitions down:

• Artificial Intelligence (AI): Refers to the simulation of human intelligence in machines to think like humans and mimic their actions. The goals of AI include learning, reasoning, and perception without human input or intervention.
• Machine Learning (ML): A subfield of AI focusing on supervised, unsupervised, or reinforced learning that enables computers to perform pattern recognition, predictions, data classification, and more without explicit programming
• Deep Learning: A subfield of ML that uses neural networks (see below for definition) to learn how to recognise images and speech or natural language processing from large amounts of data.
• Neural Network: A computational model (inspired by the architecture and function of the human brain) that consists of layers of interconnected nodes that process and transmit information. Through analysis of input data, these models can find complex relationships in data.
• Big Data: LARGE structured and unstructured data volumes that are difficult for scientists, teams, and organisations to manage or analyse using traditional techniques. 

AI in Life Science Research Lab

AI, its subfields, and big data have made inroads into many aspects of biological and biomedical science, including drug discovery and development, precision medicine, genomics, transcriptomics, and more. 

And the results are pretty impressive: Look at what AlphaFold has done for 3D protein structure prediction.

While powerful, it's still early days for AI's widespread and cavalier adoption across all areas of research and medicine. ML and DL algorithms can be subject to data bias based on the training dataset, difficulties interpreting predictions, and an overall lack of clear guidance or standardisation. 

Yes, AI's application in the life sciences feels like the "wild west," with researchers and the field needing actionable guidance.

Implementation of Artificial Intelligence in Labs: 10 Steps

As more and more labs and organisations dip their toes into AI algorithm implementation, ensuring clear documentation, reporting, and analysis is critical. Bioinformatics and data science teams need to be integrally involved as their experience with coding, IT, API, and SDK is invaluable for this task.

Another essential factor is using digital platforms for transparent and secure data management and easy integration with other computational tools, such as AI, ML, or DL programs.

At eLabNext, we live for the digitisation of all labs. And as the AI field has grown, we've seen what works and doesn't. 

Below we've synthesised ten steps to implement AI tools in your lab.

Step #1: Identify the problem or question

What are you trying to solve with AI or ML? With the problems these algorithms have been applied to, there are a growing number of off-the-shelf AI/ML solutions for data analysis and visualisation. 

For example, programs such as Modicus Prime or PipSqueak Pro can be used for image analysis; Biomage can be used for single-cell analysis; and Immunomind can be used for AI-driven multi-omics.

Step #2: Research available AI/ML software models or tools

We mentioned a few tools above, but consider accuracy, speed, and ease of use before choosing a solution. It's also essential to research the level of support, resources (such as tutorials and forums for troubleshooting), and proof-of-concept data available for the tool. 

And if there's no off-the-shelf solution, you may be forced to develop a custom model tailored to your problem.

Step #3: Evaluate your data and determine if it is suitable

Consider your data's quality, quantity, structure, and possible biases or limitations. You may need to collect additional data or clean and pre-process existing data to make it suitable for analysis. Standardisation is also crucial for this step, as it helps to ensure that the data is consistent and comparable across different sources and samples.

Step #4: Develop a testing plan to validate accuracy and reliability

Validation in the life sciences is vital for relying on a technique to generate accurate results. With AI/ML tools, you can divide your data into training and testing sets to evaluate performance. Other ways exist to test the AI/ML tool or model. Just be sure to have a plan for testing and ensure it includes testing data outliers to assess the vulnerabilities of the model or device you are implementing.

Step #5: Train your AI/ML model using the data you have prepared

If you've built an AI/ML model from the ground up, teaching it to recognise patterns or perform other tasks is the next step. The goal is to find the optimal parameters that best fit the data, minimise error, and perform well on test data.

Step #6: Test and validate your AI/ML model

Testing on a separate dataset from the one used for training is the next step in vetting an AI/ML model. This helps determine model accuracy, precision, and recall. The validation phase involves tuning the model's parameters and evaluating its performance to avoid overfitting, where the model performs well on the training data but poorly on test data.

Step #7: Integrate the AI/ML tool into your laboratory workflow

Consider how you will use the AI/ML analysis results in your pre-existing laboratory processes. The tool must be compatible with your existing infrastructure and software in the lab, particularly with any digital platforms used for information management. 

Step #8: Monitor and evaluate ongoing performance

While your AI/ML model may initially provide relevant and high-quality analysis, performance can drift, and lab priorities can change. Continuous monitoring and model updating is necessary to ensure performance metrics are met and the model is still relevant to the laboratory's evolving needs. 

Step #9: Update and fine-tune the AI/ML model

Improving performance is a crucial step in the lifecycle of an AI/ML tool or model. This can involve testing with new data, retraining with new data, and revalidating performance. You can also adjust the parameters or architectures of the models to fine-tune performance. 

Step #10: Ensure compliance

AI and ML are still new tools in the life sciences and other industries. To protect your data, adhere to regulations like GDPR and HIPAA. There are also ethical implications due to decision bias in unvalidated or inaccurate AI/ML models. To avoid these, implement a QC process involving regular performance reviews and key stakeholders.

Conclusion

AI, Ml, DL, and "big data" are here to stay in the life sciences. 

The steps above can help you and your team move toward AI implementation to answer your research questions. Off-the-shelf solutions for common research questions may exist. However, you may need to work with computational biologists and bioinformaticians to develop a new model. We recognise that training, validating, and testing a new model is no small feat: It requires focus, patience, and state-of-the-art infrastructure. For additional reading on the technical application AI/ML tools in your lab, read the comprehensive guidance from Lee et al.

At eLabNext, lab digitisation is the future and is dedicated to helping researchers, labs, and organisations implement AI solutions for deeper insights into their big data.

If you're interested in how your AI/ML models can interface with your other digital lab platforms, contact our experts at eLabNext. 

Leaders can come from anywhere within an organisation in the life sciences, where innovation and adaptation are essential. The newest research technician hired last week can be as effective at enacting widespread change through high-quality leadership as the 25-year industry veteran in the C-suite. In fact, change is often most efficiently implemented from the ground up rather than the top down. After all, the end user who has to use a new product or implement a new process daily is ultimately the best advocate for change.

So, what qualities does it take for an excellent leader to enact lasting change? 

In my experience, bringing the eLabNext digital lab platform to life science organisations big and small, I can tell you it’s no one thing. Good leadership stems from several shared attributes. Effective communication, inspiration, and others are all important, but it’s more than that. 

Here are 7 leadership qualities I’ve seen have a hugely positive impact when labs, big and small, are shifting to eLabNext’s digital platform.

Set Timelines Or Else Time Will Run Out! 

For any organisation, short- and long-term goals are critical. They provide a direction and focus for the months and years ahead and can fill lab personnel with a sense of purpose. 

To implement a new software platform (or any other change), focus on the 1-month, 3-month, 6-month, and 1-year milestones. The more specific and actionable your goals are, the better. With them, you may find yourself, your team, and your organisation more robust, with an idea of when and where to start or what success should look like. 

Here are some examples of what these goals might look like if you were adopting eLabNext’s platform:

• Month 1: Get all physical items in the lab, including storage units, instruments, equipment, samples, and supplies, digitised.
• Month 3: Digitise all protocols and projects and ensure everyone in the lab is comfortable using the new system. If they’re not, create a training plan to resolve this.
• Month 6: Everyone in the company will utilise the new platform’s features to their full potential.
• End of Year 1: Management has implemented protocols for reviewing data and analytics. The company has standardised and grandfathered in all workflows. If applicable, several automation features have been used to save time.

Of course, if you’re leading the charge on a different type of change, your goals will differ, but just be sure to set actionable, specific goals and timing associated with each.

Take Baby Steps, Get a Big Leap

One month is four weeks. That’s an average of 30 days or 720 hours or 43,200 minutes. Sometimes it doesn’t feel like it, but when you plan it, you can easily designate a few hours a week for taking the “baby steps” of setting a basic foundation and infrastructure for your new change. 

If we take our first month’s goal from above, here’s what each baby step might look like for an eLabNext implementation plan:

• Week 1: Set up all freezers and other storage units.
• Week 2: Set up all equipment and supplies.
• Week 3: Set up all sample types.
• Week 4: Import all of your legacy samples into eLabNext.

Divide and Conquer!

You can’t do everything. No leader can. 

And you don’t have to. 

Together, as a team, you have a whole arsenal of strengths. And with those, you can divide and conquer the tasks ahead of you. 

Teamwork makes the dream work, and in the case of eLabNext, the dream is to digitise your lab. 

You can divide the tasks between the people in the team, and each person can take ownership of different portions of the project, depending on their strengths. 

Felicia can do the freezers, while Steve can set up the sample types. All while Emmanuel does the equipment. 

This way, you allow many perspectives, encourage discussion and brainstorming between folks, build team camaraderie, strengthen the digital foundation, and set yourself up to be a digitally healthy and sustainable lab for years to come. 

Lead by Example

As you’re dividing and conquering, lead by example. Pick one of the weekly “baby steps” and do it flawlessly within the timeline provided. 

And if you don’t, own up to your team and find a collective solution.

This will set the tone for everyone, inspire and encourage, and solidify your group’s learnings as tribal knowledge to be passed down to all new hires. Practising what you preach and vouching for what you know can benefit the whole lab. 

Don’t Be Afraid to Ask For Help

If you’re confused or overwhelmed, going to someone for support or guidance can help you solve a problem or accomplish a task without wasting time. Asking others for help can sometimes feel weak, but all good leaders “know what they don’t know.” To continue with the example of implementing eLabNext’s platform, you can always request help from our experienced technical support (which prides itself on its expertise and customer success) or search through our resource library. 

Incentivize Key Users

Who doesn’t love a free lunch? At the 1-month mark, once all goals have been completed, you might consider rewarding key personnel that have helped you drive change. You could order food for the entire team or use the vendor (if applicable to your change) to help. 

When we’ve transitioned labs to our eLabNext platform, sponsoring a lunch and learn helps us build relationships and enables more effective communication. It also incentivises key users, which trickles downhill to inspire and motivate the rest of the team.

Review, Report, and Reap the Benefits

Review your overall progress at each milestone and report to the team. It is essential to see the change you’ve envisioned come to fruition! When we get buried in our tasks, we have difficulty stopping and smelling the roses. 

With eLabNext, the roses are your digital representation of your physical lab. Celebrate the first 100 experiments recorded. Or the first 1,000 samples created. These rewards can make it fun for people in the lab to stay encouraged and excited to keep on with everything they’re doing. 

Ready to lead the journey to digital transformation? Schedule a personal demo of our digital lab platform today!

The essence of a successful and well-functioning quality control (QC) lab lies in the name itself. Achieving, maintaining, and continuously improving quality is the ultimate goal in ensuring patient safety. 

So, how can regulated labs maintain these high-quality standards and successful processes?

Many factors – such as those defined in ISO 15189:2012 or by the Clinical & Laboratory Standards Institute (CLSI) – play a role in QC lab operations. This blog focuses on managing sample and inventory processes, data, documents, and records and how digital software platforms play an essential role. 

QC Lab Requirements and Challenges

QC labs handle and process many samples, ranging from raw materials to in-process samples, drug products, and finished products. As these samples are analyzed, large amounts of data are generated, including QC test results, calibration reports, and more. 

Properly managing the sample chain of custody and associated specifications is critical for consistently high quality. And, not surprisingly, it comes with challenges.

As lab personnel processes samples and runs release testing of materials and samples, the data must be managed to ensure all information is accurate, accessible to qualified personnel, secure and traceable. 

Let’s go through some common difficulties with the samples, inventory, data, documentation, and records management process.

Sample and Inventory Management

Every step in the sample collection, handling, and testing process must be carefully controlled and tracked by QC personnel. In addition, QC lab testing methods and the overall process must be verified and validated. Inventory management is similar: the procedures for raw materials, reagents, equipment ordering, storage, and expiration must be controlled and tracked.

Many QC labs accommodate large volumes of samples daily. A significant challenge is processing, tracking, maintaining accurate records, and ensuring all samples are correctly handled.

Inventory management is another challenge in QC labs, as keeping track of supplies, equipment, and chemicals can be time-consuming and complex. Guaranteeing the required materials are in stock at the right time and stored in a way that protects integrity can be a constant difficulty. If they aren’t correctly managed, there is a risk of incorrect or expired materials being used, which can impact the quality of results. Furthermore, ineffective tracking of usage and ordering trends can lead to inefficient spending.

Data Management

Data accuracy, reliability, and timeliness are essential for QC. Accomplishing this takes rigorous attention to the evolving regulatory requirements for data management, such as electronic signatures, 21 CFR Part 11 compliance, and data backup and recovery processes.

With a combination of manual testing procedures and automated instruments, several challenges related to data management emerge. This includes assuring the security of sensitive information and avoiding data loss due to system failures or human error. Another challenge is integrating data from different sources and formats into a centralized database that supports downstream data analysis and reporting in a robust, flexible way.

Document and Record Management

On top of data management, lab standard operating procedures (SOPs), protocols, and test records must be securely managed. This requires proper storage and access controls to prevent unauthorized access, tampering, or data breaches. In addition, consistent adherence to established procedures and practical training and personnel monitoring is essential for maintaining the integrity of the testing process, demonstrating compliance with regulations, and supporting continuous improvement in QC labs.

Overcoming QC Barriers with Digital Laboratory Platforms

Digital lab platforms (DLPs) ameliorate the sample tracking and data management woes discussed above. They proved a standardized, comprehensive approach to most QC processes, reducing the risk of errors, providing a fully traceable account of lab operations, improving overall efficiency, and ensuring regulatory compliance.

Here’s how:

• Centralized and standardized QC operations: DLPs enable digital record keeping for tracking and managing all samples, inventory, data, documents, and records. It also implements a process for the consistent execution of workflows, reducing the risk of human error.
• Thorough regulatory compliance: Many DLPs offer automatable processes, full traceability, and audit-ready capabilities. Organization of the abovementioned information (e.g., samples, inventory, data, etc.) in a centralized place also helps drive compliance by maintaining accurate records, automating processes, and enabling a transparent ‘birds-eye view’ of laboratory operations.
• Streamlined reporting: A DLP can facilitate creating a transparent and reliable reporting process to communicate valuable quality information to all relevant stakeholders. Furthermore, reporting can be automated, enhancing the overall efficiency of the lab and supporting more confident decision-making.
• More secure data: DLPs provide a highly secure framework for implementing and maintaining safe processes for collecting, storing, and sharing information. Most DLPs have access control, encryption, backup, and disaster recovery capabilities.

Try eLabNext’s DLP for Your QC Needs

Digital platforms help solve typical sample tracking and data management challenges in a QC environment.

Book a personal demo today to see how eLabNext’s DLP fits into your QC lab!

The NanoPhotometer family are microvolume spectrophotometers designed to measure single or multiple liquid samples of small volumes with high accuracy and precision. With the ability to measure as little as 0.3-2 µl of samples, researchers can save time and precious samples while ensuring accurate results.

Seamless data flow 

Mistakes can easily happen when manually copying and pasting data, especially when dealing with large amounts of information. Automating this process can help eliminate the risk of human error and ensure data is accurately transferred to your Digital Lab Platform (DLP). The Implen NanoPhotometer add-on allows users to automatically store all measurement data from their connected NanoPhotometer(s) directly in eLabJournal. This add-on reduces procedural errors and increases consistency and traceability across multiple users and samples.  

The Implen NanoPhotometer add-on streamlines user workflows, making it easier to manage and analyse data. By having measurement data automatically transferred to eLabJournal, users can easily track and organise data over time. This can be especially beneficial for researchers and laboratory technicians who need to manage large amounts of data and track changes.  

By saving time, reducing the risk of errors, and providing a streamlined workflow, this add-on can help users efficiently manage and analyse data, ultimately leading to more accurate and reliable research results. 

What makes Implen NanoPhotometers unique 

The unique family of instruments offer a wide range of pre-programmed apps for scientists in research, education, development and quality control applications within universities, research institutions, biotech and pharma companies. 

They scan from 200 – 900 nm in less than three seconds, covering 1 – 16,500 ng/µl dsDNA concentrations or 0.03 – 478 mg/ml BSA. 

Automatic detection of contaminated samples ensures accurate results. Intuitive touchscreen operation, integrated vortex, simple pipette-measure-wipe-repeat workflow, small footprint and network integration for convenient lab bench operation. Recalibration-free patented technology--made in Germany. 

The Implen NanoPhotometer N120 scans up to 12 samples in just 20 seconds. Quantifying DNA, RNA, and proteins have never been faster. Increase your sample throughput and measure a 96-well plate in just 5 min. Less pipetting means fewer errors. 

The new Implen NanoPhotometer add-on is now available and free to install from the eLab Marketplace. Schedule a personal demo with the Implen team to test the add-on, or visit the Implen website to learn more about the technology. 

About Implen 

Implen is a privately held corporation leading supplier of spectroscopy instruments and consumables for the non-destructive analysis of ultra-low volume samples. The company focuses on biological, chemical, and pharmaceutical laboratories in industry and research. Implen strongly focuses on the customer, taking pride in providing quality products and high customer service to achieve total customer satisfaction. 

implen.com

For any questions, please contact Soeren Rowold at leads@implen.de.

The healthcare industry has recently seen a significant shift toward electronic patient records. One key protocol to facilitate this shift is HL7, which stands for Health Level 7, created by a non-profit organization called Health Level Seven International. 

The set of standards simplifies how electronic data is shared between different digital healthcare platforms and makes it easier and more efficient for healthcare providers to share patient data.

What is HL7?

HL7 sets international standards for exchanging, integrating, sharing, and retrieving electronic health information. 

Data formatted using the HL7 standard capture patient data in a unified and easily transmissible format. This digital message can be quickly sent between different software programs, enabling communication between platforms in a friendly, error-free, autonomous fashion. HL7 encompasses several essential standards, including:

• HL7 v2: This widely used standard defines the structure and content of messages exchanged between healthcare systems, facilitating interoperability and data exchange.
• HL7 v3: Designed for more complex healthcare scenarios, HL7 v3 provides a framework for creating detailed clinical and administrative models to improve interoperability across different systems.
• HL7 FHIR (Fast Healthcare Interoperability Resources): It is a modern and rapidly evolving standard that focuses on simplicity and web-based integration, enabling seamless exchange of healthcare data across diverse systems and platforms.
• HL7 CDA (Clinical Document Architecture): It specifies the structure and semantics of clinical documents, allowing healthcare information to be exchanged in a standardized format that supports interoperability and meaningful use.
• HL7 CCD (Continuity of Care Document): It is an HL7-compliant standard that provides a snapshot of a patient's health information, facilitating the exchange of relevant data for continuing care and transitioning between healthcare settings.

These HL7 standards play a crucial role in achieving seamless interoperability and efficient exchange of health information in the digital healthcare ecosystem.

What Types of Labs Use HL7 Messages?

The use of HL7 in healthcare is widespread, and any lab that exchanges patient information will need to send and receive HL7 messages using digital platforms.

Here are several types of labs that use HL7 messages:

• Clinical testing labs: Clinical labs test biospecimens collected from patients to diagnose or monitor medical conditions or the effectiveness of treatments. In this context, HL7 communicates test results and patient information between a clinical lab and other healthcare systems.
• Pathology labs: Similar to clinical testing labs, pathology labs perform tests on tissues or other biospecimens to diagnose disease. HL7 helps exchange test results with other healthcare systems.
• Blood banks: Information about blood donors, blood collection, and blood testing is exchanged using HL7 to communicate the results of blood tests or other patient information to ordering systems.

HL7 may also be used to exchange data with research (and many other types of) labs performing studies on patients.  

How is HL7 Used in the Healthcare Industry?

HL7 provides a standardized and interoperable way for labs to exchange information with other healthcare systems, improving the accuracy, efficiency, and quality of patient care.

Here are some ways HL7 is used in the healthcare industry:

• Interoperability: HL7 enables interoperability by providing a common language and framework for different healthcare systems to communicate with each other. It ensures that data can be exchanged accurately and consistently across diverse systems, including electronic health record (EHR) systems, laboratory information systems, radiology systems, pharmacy systems, and more.
• Patient Data Exchange: HL7 allows for the exchange of patient data between healthcare providers, hospitals, clinics, and other entities involved in patient care. This includes essential information such as patient demographics (name, age, gender, address), medical history, allergies, medications, and clinical observations.
• Clinical Messaging: HL7 defines a messaging standard that enables the transmission of clinical information, such as laboratory test results, radiology reports, and other diagnostic findings. This helps healthcare providers to access and review patient information efficiently, supporting timely decision-making and providing better quality care.
• Integration with Electronic Health Records (EHRs): HL7 plays a vital role in integrating various healthcare applications with EHR systems. It enables the seamless flow of data between different systems, ensuring that information from laboratory tests, procedures, and other sources is accurately captured and stored in the patient's electronic health record.

How the eLabNext Platform Receives HL7 Messages

eLabNext, a digital lab platform used by a wide array of laboratories that allows tracking of sample information and test results, can receive HL7 data messages within a user’s digital lab space and translate this into a sample record for processing.

This capability allows your lab to seamlessly receive physician testing orders, complete with a unique barcode identifier. The automated process reduces data loss and errors as the lab processes samples.

Any laboratory personnel can use eLabNext to track sample processing and continuously update it with testing results. Using this intuitive digital lab platform, you can easily associate your results with specific patients. The lab can send this back to the ordering system as another HL7 message when the results are complete. Full traceability enables a comprehensive audit trail.

We have established this automated loop with Point & Click Solutions and Enterprise Health’s electronic health record (EHR) systems to track and manage patient COVID-19 testing. This integration tracked a high volume of daily patient samples while managing test results and routing them back to these EHR systems. 

eLabNext also used similar capabilities to support Boston University’s in-house COVID-19 testing workflow, processing up to 9,000 samples daily.

The Details for IT Folks…

We use a REST API POST message to enable connections between platforms. The message header contains the mapping instructions for translating the HL7 fields into a sample. This allows for a very nuanced setup precisely tailored to each lab.  

Here’s what an example header looks like:

{

"sampleTypeID": 12485,

"storageLayerID": 0, /* Optional */

"position": 0, /* Optional */

"name": {

"segment": "MSH",

"field": 10

},

"description": { /* Optional */

"segment": "MSH",

"field": 9,

"component": 3

},

"altBarcode": { /* Optional: Alternative barcode information. */

"segment": "OBR",

"field": 31

},

"sampleTypeMetaIDMapping": [ /* Optional: Array of mappings for the sampleTypeMetaID to the respective segment in the HL7 message */

{

"sampleTypeMetaID": 85318,

"segment": "OBX",

"field": 5

},

{

"sampleTypeMetaID": 85317,

"segment": "ORC",

"field": 2

}

]

}

And if You’re Not Technically Inclined, No Worries

The above is JavaScript code that represents a configuration for a sample type in HL7 messaging. But if you’re not an IT professional, all you need to know is:

• HL7 simplifies the sharing of patient data between different digital platforms, making it more efficient and error-free for the life science industry. 
• HL7 is widely used in diagnostic testing labs and donor banks to exchange patient information and/or test results. 
• The eLabNext platform receives HL7 messages, allowing laboratories to process samples automatically with unique barcode identifiers. 

Overall, HL7 is crucial for digital laboratory environments.

If you’re interested in learning more about eLabNext’s platform and HL7 messaging, schedule a personal demo to see how it works.

Los Angeles, California – The digital transformation of the life sciences industry continues apace, with Lab Digitalization at the top of the priority list. With the opening of eLabNext's new office in Glendale, CA, the area is ideally placed to emerge as a hub for innovation and entrepreneurship.

Eppendorf's eLabNext division was founded in 2010 with the goal of streamlining life science R&D by digitizing laboratory processes. The company offers a full-service experience with a team of experts who help clients along their digitization journey. eLabNext solutions have been used in a variety of research areas, including cancer research, sustainable food production, and the development of the COVID-19 vaccine.

"We are thrilled to open our new office in Glendale and join the vibrant community at Hero House," said Alisha Simmons, Key Account Manager at eLabNext, Americas, division of Eppendorf. "This move represents a major step forward in our mission to streamline life science R&D through digitization and make a positive impact in the industry."

A thriving community of startups and innovation leaders surrounds the new office at Hero House. SmartGateVC, a Los Angeles-based pre-seed and seed venture capital firm investing at the intersection of AI, Healthcare, and Biotech, founded Hero House as a startup and innovation hub.

"As we continue to expand globally, we are excited to open our new office in Glendale and become part of Los Angeles' thriving life sciences community," said Erwin Seinen, Founder and Managing Director at eLabNext.

Hero House provides the infrastructure and resources needed to power the growth of new ventures through its programs, global mentor network, angel investor group, and technology transfer support. 

"At Hero House, we are committed to cultivating a vibrant community of innovation and entrepreneurship in the life sciences industry. The arrival of eLabNext to our tech entrepreneurship hub opens up a wealth of opportunities for SoCal startups and labs and strengthens our ecosystem. Their commitment to digitizing laboratory processes aligns with our mission, and we look forward to assisting eLabNext and their clients as they continue to drive progress in this exciting field." Ashot Arzumanyan, Partner, SmartGateVC

The benefits of digitization are becoming more apparent as life science labs continue to adopt new technologies. Modern labs are streamlining their operations and allowing scientists to focus on their research by automating manual processes, minimizing data errors and improving data storage, AI-optimized processes, and more. The life sciences industry's future appears bright, with many promising players emerging in SoCal.

The opening of eLabNext's new office at Hero House demonstrates the growing importance of digitization in the life sciences and the promising future of Los Angeles' biotech scene. The area is poised to become a hub for life science R&D and biotechnology, with a thriving community of startups, innovation leaders, and an increasing number of key players entering the market.

eLabNext contact

Alisha Simmons, Key Account Manager at eLabNext, division of Eppendorf, 508-851-7747, a.simmons@elabnext

About SmartGateVC and Hero House

​SmartGateVC is a SoCal--and Armenia--based pre-seed and seed venture capital firm investing at the intersection of AI with healthcare, biotech, security and IoT across Southern California, the wider U.S., and Armenia. SmartGateVC provides startups with the resources and support they need to succeed, thanks to a team of experienced investment professionals and a global mentor network.

​​Hero House by SmartGateVC is a startup and innovation hub in Glendale, CA, where SmartGateVC works with scientists, founders, executives, and co-investors to turn research and technology into various disciplines into industry-defining companies. It connects science, technology, entrepreneurship, and capital, fostering the creation and advancement of new ventures.

smartgate.vc and herohouse.io   

Liana Karapetyan, Associate at SmartGateVC, Director of Hero House Angels, liana@smartgate.vc 

ASCENSCIA is your voice assistant in the lab, specifically designed for scientists by scientists. It essentially functions as your companion, providing an easy way to access information and record data while working in the lab, freeing up your hands and allowing you to focus on your experiment.

The digitisation of scientific laboratories is ongoing and often challenging. One hurdle scientists face is staying connected with their electronic lab notebooks (ELNs) from the bench. With multiple experiments to perform and data to record, multitasking can lead to wasted time and valuable research information being lost. However, the emergence of voice assistant technology developed by ASCENSCIA for scientists offers a solution. The ASCENSCIA voice assistant allows for the hands-free recording of notes and data directly into the eLabNext platform, streamlining the research process and aiding in the complete digitisation of labs. By simplifying daily tasks and eliminating manual note-taking, scientists can focus on their experiments and make the most out of their time in the lab. This technology revolutionises traditional methods, leading to more efficient and accurate scientific research.

Inefficiencies that lead to wasted resources and slow down lab digitisation

Working closely with research labs in academia and industry, we gained insight into the hidden inefficiencies that lead to wasted resources and slow digitisation. Scientists often feel frustrated by their inability to easily access or transfer data, particularly from paper notes to electronic lab notebooks (ELNs). These small obstacles can add up, hindering overall productivity in the lab. Our collaboration with research labs allowed us to identify and quantify these inefficient processes, ultimately leading to the development of the ASCENSCIA voice assistant. For example, addressing disconnected access to electronic lab notebooks and streamlining data transfer from paper notes can save significant amounts of time and improve data quality. In fact, our efforts have increased productivity by 40%, saved researchers up to 30% of the time, and reduced reproducibility issues by 70%.

I believe that this is a very interesting time for the scientific research field, moving towards lab digitization. It is very exciting to work together with partners like eLabNext to accelerate this transformation process.

Ahmed Khalil, Founder & CEO at ASCENSCIA

A fruitful partnership

At ASCENSCIA, we carefully select our partners to ensure that we all work towards the same goals and values. That’s why we chose to align with eLabNext – their mission to digitise scientific laboratories aligns perfectly with ours. Not only that, but their products and services make it easy for us to integrate our voice technology solution into labs. We were thrilled by the enthusiasm and support of the eLabNext team during our partnership explorations – all signs pointing to a successful collaboration. We are excited to see what the future holds for our partnership with eLabNext.

At eLabNext, our mission is to revolutionise life sciences research by building an expansive marketplace of customisable digital lab tools. That's why we're thrilled to announce our partnership with ASCENSCIA, a company dedicated to creating groundbreaking voice assistant technology designed specifically for scientists. By integrating this technology into our platform, we can offer even more options for researchers to streamline their workflows and make thier day-to-day lab tasks easier than ever before. We're excited about the potential this partnership brings and can't wait to see how researchers take advantage of this innovative new tool in their labs.

Lara Matthews, Business Development Manager at eLabNext

About ASCENSCIA

ASCENSCIA is a highly specialised voice assistant for scientific labs. ASCENSCIA can integrate seamlessly with existing databases, systems and machines in the lab, making them smarter by creating voice-enabled labs. Accordingly, scientists can collect data accurately, automate experimental workflows and stay connected to their databases from the lab just by the power of their voice.

We are a team of scientists who know the struggles, challenges and costs of bringing drug therapeutics to the market. Our mission is to shift scientific research towards a more data-driven era. We accelerate early-stage drug discovery research into a more efficient, economical, and sustainable process. Simply, solving the small day-to-day challenges in the lab collectively contributes to the tremendous waste of lab resources. Ultimately, we aim to transform scientific research labs into more data-centric and data-driven.

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Here are some of our highlights from 2022 and some updates for 2023.

2022 was an excellent year for eLabNext

In 2022,

• We welcomed more than 200 new customers
• We had 63 product releases. 12 of which were significant features

Thanks to feedback from all our customers, we were able to work on several features and improvements.

Here are our most important releases from 2022…

Auto-incremental sample naming

Unique sample names can now be automatically generated based on an incremental number, supplemented with a custom prefix and suffix. The generated sample name can also be applied as the barcode or used in a custom sample field.

Assigning Tasks

We introduced the ability to create and assign tasks to users. Users will be notified when tasks are assigned to them. The Tasks Add-on is available to all users and can be installed for free in the Marketplace.

Electronic Signatures with Single Sign-on

Customers with Private Clouds and On-Premises installations that use Single Sign-On may now sign experiments with their organisation login.

Custom Protocol Categories

Groups may now create custom protocol categories to organise their protocols.

Marketplace improvements and new integrations

eLabNext's openness to integrate with other 3^rd party products and services makes it unique. In 2022, the following ten add-ons were released in eLab Marketplace:

• ImmunoMind
• mpVision
• Eppendorf VisioNize Sense
• FLUICS PRINT
• CloneAssist – BETA
• ChemAssist – BETA
• Tasks
• Box
• Pipsqueak Pro
• Clustermarket’s equipment scheduler
• Enhanced LaB Execution – BETA

We are happy to see that more customers are taking advantage of our API and SDK to extend the functionality of eLabNext according to their needs and build private add-ons. As part of our strategy of being an open ecosystem platform for life science labs, we will continue to work with other 3^rd parties to bring many more new add-ons to our marketplace.

Please visit our Product Updates page to see all updates released in 2022.

What to expect in 2023...

We have been working hard to complete a revamp of our sample Management functionalities. We plan to release this in 2023. In addition to the great new look, we worked on improving the usability of the Inventory Browser to support the following new features:

• Support for drag and drop to move samples
• Custom List views in the Inventory Browser
• Collapsing of sample series

Finally, we would like to thank you all for your continued support in 2022 and look forward to continuing to support you in 2023.

Best wishes for the New Year!

The eLabNext Team

Biobanks have become essential providers of valuable biospecimens and associated metadata, empowering researchers to perform large-scale genetic studies, develop personalized therapeutics, and answer global questions. With the growth in biobanking and its foundational role in research, an increasing number of biobanks are using digital platforms, such as laboratory inventory management systems (LIMS), to organize their collections of biospecimens, handle day-to-day operations, track trends in activity, and more. 

But, there are many LIMS software options for biobanking. And not all of them are created equal. 

Choosing an appropriate platform for your needs can positively impact your biobanking operations' efficiency, accuracy, and success. Therefore, it’s vital to ask critical questions when evaluating biobanking LIMS providers. 

Take a look at these 6 key questions to help you assess whether or not a LIMS software for biobanking is right for you.

Question #1: How does the Software Handle Sample Management and Tracking?

A well-designed sample tracking and inventory management system can significantly improve the efficiency of your biobanking operations by providing a “birds-eye-view” of your entire collection. Any software you’re considering and evaluating should provide a centralized system for managing any type of biospecimen (and associated metadata or documentation) within your biobank, control the distribution of biospecimens to researchers, integrate with all other software (e.g., electronic lab notebooks) or equipment (e.g., ultra-low temperature freezers), and find space for new biospecimens. All entries should have full traceability so that they are audit ready and can be understood by the appropriate personnel.

Question #2: Does the software have a user-friendly interface that is easy to navigate?

A user-friendly interface should be intuitive and have a logical layout for the LIMS functionalities. This makes it easy to find the necessary information and perform tasks without extensive training. The software should also have clear and concise instructions that can help users to understand how to use the software efficiently. For more advanced features, make sure that technical support and training are provided by any LIMS vendor you are considering (see the next question below).

A favourable and easy user experience can increase adoption and satisfaction, which can improve the biobanking operation's overall success.

Question #3: Does the Software Vendor Provide Training and Customer Support?

Adequate training and customer support can ensure that LIMS software is used correctly and that any issues are quickly resolved. Vendors that provide training and support across the LIMS lifecycle help improve biobanking operations' efficiency by arming users with the information they need to succeed while using the LIMS.

The software vendor should train all staff on using the software, including hands-on training, online tutorials, and documentation.

Additionally, the vendor should provide ongoing support to assist with issues arising after the software is implemented. Make sure that you have access to the technical support team 24/7, so whenever a problem comes up, you have the help you need. You can put this to the test during trial periods, which most LIMS vendors offer for 30 days at no charge.

Another way to learn more about LIMS technical support, software performance, and overall reliability is to check in with current platform users and ask them about their strengths or weaknesses.

Question #4: What is the Transition Process from Our Legacy System to a New LIMS?

Transitioning from a legacy LIMS, platform, or bootstrapped solution to a new LIMS can be difficult. To ensure a smooth transition, it is essential to evaluate how a new vendor and system can support the process. 

Begin by assessing your current system and identifying all essential data that needs to be transferred to the new system. Then, ask the vendor's support staff about how the new system can accommodate this data and how you can import it in a format that the new system can understand. Ask for a demonstration of how this process works, and if you end up purchasing a new LIMS, be sure that you’ve carefully vetted the technical support team (described in the section above) so that they can walk you through the process and identify any potential problem areas.

Question #5: How does the Software Handle Data Security and Privacy?

Data security and privacy should be top priorities when considering LIMS for your biobanking operations. The software needs robust security features such as encryption, user authentication, and access controls to protect against unauthorized access and data breaches. It should also comply with regulations such as 21 CFR Part 11 and GxP guidelines to ensure that the data is handled and stored in a compliant manner.

Furthermore, audit trails and reporting capabilities to track and monitor data access can help detect and prevent any security breaches, a necessary feature for a biobanking LIMS. The software should also be able to back up and restore data in case of accidental or malicious data loss.

Question #6: Is the Software Scalable, and Can it Accommodate the Future Growth of the Biobank?

Scalable LIMS software for biobanking can accommodate future growth and handle an increasing number of samples, users, and complex data sets.

To ensure that the LIMS you are considering can scale up or down as needed, assess if the platform can be cloud-based and integrate with other systems, such as extra storage solutions, which can help handle the increasing amount of data generated by the biobank.

Additionally, expanding functionality through add-ons and tracking activity trends are two powerful features that can help inform growth opportunities and maintain performance and reliability. The former can allow more rapid and accurate sample management and tracking, while the latter can help personnel make strategic decisions about equipment purchases.

How Do You Make a Decision About a Biobanking LIMS Provider?

Getting answers to the questions above is essential to educate yourself about the strengths and weaknesses of the various software solutions available.

If you want to learn more about finding a digital platform that’s right for your biobanking operation, download our biobanking guide, “​​How to Choose the Best Digital Platform for Your Biobank: A Complete Guide to Avoiding Digital Chaos and Streamlining Your Operations.”

You’ll learn about:

• The ins and outs of modern-day biobanking
• What key challenges do biobanks face, and their impact on operations
• How to overcome common barriers in biobanking using a digital lab platform
• A step-by-step process for evaluating a biobanking software vendor
• How eLabInventory can streamline your biospecimen management process
• Why the Musculoskeletal Oncology Lab (MOL) at the University of Pittsburgh uses eLabInventory

Working in biotech or pharma means performing research, advancing candidates to market, and manufacturing products in compliance with regulatory guidelines, collectively known as GxP principles.

The “x” is shorthand for specific environments, including the laboratory (good laboratory practices; GLP) and manufacturing facilities (good manufacturing practices; GMP). GxP guidelines help ensure that data is managed correctly and that products like pharmaceuticals are manufactured with safety, efficacy, and quality in mind. Yet, complying with these guidelines requires rigorous documentation.

GxP Compliance Challenges

Adapting to GLP and GMP guidelines can be challenging for labs transitioning their operations from unregulated environments: Voluminous paper records require physical storage space, are not always immediately accessible, and require time and effort to store, secure, and manage.

These hurdles can have detrimental effects on the integrity of data (i.e., which ensures the reliability of data) collected in GxP labs or facilities. It can also negatively impact the traceability (i.e., the ability to reconstruct the development history of a product, such as a drug or medical device) and accountability (i.e., the ability to resolve who has contributed what to the development and when) of information, two key characteristics necessary if regulatory authorities need to conduct an audit.

How to Solve GxP Issues with ELNs

To control these issues, web-based laboratory management software like an electronic laboratory notebook (ELN) can help manage traceability, accountability, and data integrity, three pillars of GxP compliance.

Many software options offer flexible platforms that facilitate the efficient flow and secure storage of information, keeping track of data, samples, inventory, and other critical details.

These functions are necessary for various aspects of GxP compliance and are commonly deployed to help labs and manufacturing facilities manage this process. In turn, GxP guidelines outline several requirements for those using ELNs or other software solutions.

Let’s look at GLP and GMP principles, what they are, and how ELNs can help promote regulatory compliance.

What is GLP Compliance? How Does it Apply to ELNs?

GLP (Good Laboratory Principles) guidelines are a “quality control system covering the organizational process and the conditions under which non-clinical health and environmental studies are planned, performed, monitored, recorded, reported and retained.”

The FDA uses GLP principles as a framework for efficacy and safety testing of pharmaceutics, veterinary drugs, cosmetic products, and other similar products.

GLP guidelines apply to personnel, facilities, protocols, standard operating procedures (SOPs), biological and chemical materials, and reporting, storage, and retention of data involved in a study.

Below, we outline three vital GLP principles that apply to ELNs and their use to manage digital data.

GLP Compliance Principle #1: Data security and integrity

Raw data, including photographs, computer-readable media, observations, recorded data from automated instruments, and any other data storage medium, must be securely stored and protected from unauthorized access, changes, and loss.

Data also needs to be protected from any unauthorized modifications. Any changes must be fully auditable, with a timestamp, associated personnel, and electronic signature.

GLP Compliance Principle #2: Validation of software

Any software or computer system that stores and retains data must be fully validated, operated, and maintained for experimental studies. GLP laboratories also need to ensure that any validated ELN software is supported through regular maintenance, technical aid, performance review, and training to ensure that ELN software is being used correctly and continues to comply with GLP principles.

GLP Compliance Principle #3: Archived data

Digital data should be archived so that personnel can easily access it, in a readable format, throughout a time period specified by regulatory authorities. Permission and access also must be restricted to authorized users.

What is GMP Compliance? How Does it Apply to ELNs?

GMP (Good Manufacturing Practices) and principles help to ensure the quality and safety of a product through defined requirements for the methods, facilities, and controls used in the manufacturing, processing, and packing of a product. GMP guidelines apply to pharmaceutical or biotech companies manufacturing products for human or veterinary use.

Much like in the GLP guidelines, GMP guidance has specific regulations for electronic data management, comprehensively outlined in Title 21 CFR Part 11, the FDA regulations on Electronic Records and Electronic Signatures.

This guidance document states, “Part 11 applies to records in electronic form that are created, modified, maintained, archived, retrieved, or transmitted under any records requirements set forth in Agency regulations.”

Below are some of the essential GMP principles, as outlined in Part 11, that you’ll need to comply with when managing electronic data with an ELN.

GMP Principle #1: Validation

The FDA has published a detailed software validation process that helps to ensure that any platform used is qualified for its intended purpose. Validation can be broken down into three distinct processes:

• Installation qualification, which asks if the software is installed correctly
• Operational qualification, which asks if the software complies with requirements outlined in Part 11
• Performance qualification, which asks if the software reliably produces results while operating

GMP Compliance Principle #2: Audit trails

Electronic records must be fully auditable by regulatory bodies, such as the FDA. That means a historical account of all electronic records and associated activities needs to be kept and maintained.

In doing so, all records become easily traceable: If the FDA conducts an audit, they can determine what actions (creation, modification, or deletion of data) were taken, at what time, on what date, and by whom.

Therefore, all personnel must have defined user roles and appropriate permissions within a software system to ensure documentation of all activities.

GMP Compliance Principle #3: Data security

An added benefit of traceability and audit trails is increased data security, a major element of Part 11 guidance. Defined user roles and permissions ensure documentation of the responsibilities and activities of all personnel involved and access only to relevant electronic information.

Password protection also improves digital security for any information stored in an ELN. Many platforms have improved security through two-step authentication, adding an extra protection layer to user accounts.

GMP Compliance Principle #4: Record retention and copying

Part 11 requires that personnel ensures “...the protection of records to enable their accurate and ready retrieval throughout the records retention period.” It also requires that human-readable copies (PDF or XML) can be made from any electronic records.

Many ELNs enable comprehensive record-keeping through manual entry, equipment or software export, or linked files. Electronic signatures (so long as they are associated with an individual) can be implemented for review or approval of records, such as standard operating procedures (SOPs), and subsequently locked so that they cannot be modified or accidentally deleted. Typically, all file versions are stored and are always recoverable to make a human-readable copy. Locked digital data can be saved in a PDF format and stored in a separate electronic location as an archive.

Finding a GLP/GMP-Compliant ELN

Regardless of the regulatory environment you find yourself in, compliance is a necessary part of ensuring the safety, efficacy, and quality of experimental, non-clinical data and/or manufactured products.

eLabJournal enables users to track and manage SOPs, digital data, samples, and inventory associated with working in highly regulated markets. It is a GLP- and Part 11-compliant ELN with a robust history of success in the biotech and pharmaceutical industry.

Laboratory personnel and regulators can search eLabJournal and view the timeline for any study or record, including any change management activities. It further enables users to have a clear map of the flow of operations, whether those operations are inputting new data, archiving data, updating sample quantity, designating equipment usage, or signing off electronically on a report or experiment.

Our software includes multiple features that support GxP compliance:

• Audit-ready traceability: Built-in audit trails automatically track and log every activity by each user.  
• All electronic records, one platform: Data inputs can be entered in multiple ways for comprehensive record keeping, including manual entry, uploads from equipment or other software, and linking files stored elsewhere on a computer.  
• Reliable signatures: Once an experiment has been electronically signed and locked, its corresponding data cannot be modified.
• Trusted record retention: All file versions are stored and always recoverable. Record retention is ensured by preventing users from deleting data.
• Easy archiving: Experimental reports saved in a PDF format are stored in a separate electronic location. Standard operating procedures (SOPs) can be easily stored and referenced.
• Safe and secure data management: Defined user roles and permissions ensure documentation of the responsibilities and activities of all personnel involved.

If you’re searching for a GxP-compliant ELN solution, schedule a personal demo today.

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The number of open-source and commercially available ELNs has exploded over the past decade, making labs in academia, industry, and government more streamlined, cost-effective, and organised. But, many labs still haven’t transitioned to digital information storage, choosing paper lab notebooks or an assortment of legacy systems for data management. Scientists, technicians, lab managers, and other personnel may be comfortable using these outdated approaches. Still, the consequence of not modernising your life science operations can be dire: Your lab or organisation may lose data, protocols, or samples. Ultimately, this can cause reproducibility issues or make it challenging to keep up with the current scope, breadth, and pace of research.

Resisting the Adoption of an ELN

Transitioning away from old, familiar systems remains a significant challenge for those looking to modernise. In the life sciences, we often pride ourselves on logic and reason. But when it comes to changing entrenched habits, we can be highly resistant, even to change that brings numerous advantages. While the pain points and perspectives may differ within teams, the reasons for resisting the adoption of and transition to an ELN come down to 6 common factors. Below, we discuss each reason for resistance and how you can help your organisation overcome these barriers to digitization.

Reason for Resistance #1: Lack of Information

While the COVID-19 pandemic accelerated many companies’ digital transformation, for many in the life sciences, there is still a lack of tangible information about digital health, data accessibility and security, lab sustainability, compliance, and how this all relates to information management. Intuitively, many know the advantages of digitising, but it’s unclear how software solutions, like an ELN, will help implement these initiatives. The “what” and “how” of digitization is still a black box.

Overcoming a Lack of Information

The cure for lack of information should be education, right? It may sound easy, but humans are not empty vessels into which data can be poured. Groundwork needs to be laid first. You can lay a crucial foundation for education as a small lab or large organisation by getting team buy-in on your needs for an ELN. Do you need something easy to use? Can you dump your old Excel docs and existing digital information into it? Work out all of this before you start investigating vendors. Prioritise your needs, and you’ll enter the evaluation process focused on what is essential for your organisation.Once you’ve started investigating vendors, then education about the various benefits of their platforms and how they fit into the digital ecosystem can begin. Vendors can be accommodating in this task, helping fill in the blanks by providing demonstrations and informative content. While essential, this educational step can introduce another major pitfall: Due to the many unknowns and over 80+ ELN/LIMS systems out there, a small biotech start-up or an academic lab can easily fall victim to going for the very first available system or the complete opposite, fall into the trap of endless evaluations of which solution fits them best and in turn, lose track of their agreed-upon needs.Beware of this pitfall and only gather information with your platform requirements clearly defined.

Reason for Resistance #2: Lack of Time

In today’s fast-paced digital world, time to do even simple tasks can seem non-existent. So, it’s no surprise that personnel and whole organisations would resist a change requiring a serious time commitment to learn a new software platform. As the article “How to Deal with Resistance to Change” in the Harvard Business Review put it, “Time is necessary even though there may be no resistance to the change itself.”

Overcoming a Lack of Time

This is where the expertise of the vendor you choose can help. Whether you’re tracking thousands of samples in a biobank, developing processes for CAR-T manufacturing, or managing gene editing protocols, experienced customer service reps who have helped many organisations transition to their platform can quickly understand your workflows and needs. Their role is as a consultant to streamline implementation and shorten the learning curve for your team, adding as little time as possible to the transition process.

Reason for Resistance #3: A Painful Learning Curve

Acquiring any new skill – whether you’re learning how to ride a bike, pipette with precision, load an HPLC, or use Zoom for an important meeting while your children and dog are jumping up and down in the background – takes time. As a person gets more experience with a new skill, their proficiency increases. This process, the learning curve, is unavoidable and can be frustrating for those navigating its early stages. The size of an organisation can dictate how steep or shallow the learning curve is: A laboratory of 2 people can adjust easier, whereas a larger biotech company of 20, 30, or 100 people can take a serious productivity hit while transitioning to a new information management system. And this productivity loss can be a costly hidden expense of transitioning.

Overcoming a Painful Learning Curve

It takes a good leader, strategic planning, and an enthusiastic vendor to make the learning curve as short as possible. From a management perspective, it’s helpful to estimate the loss in productivity that’s bound to occur, so you’re not blindsided as your team navigates the platform change. For those adopting and using a new platform every day, it can be helpful to “start backward,” focusing on the bliss of the end result rather than the new, unfamiliar features of the tech itself. Thinking about the benefits of adopting new technology – in the case of an ELN, it's to elevate your research/process development – is always a good motivation to quickly learn the system and start reaping the benefits as soon as possible, without feeling like they’re diving into the unknown.

Reason for Resistance #4: Fear of the Unknown

Leaving behind paper notebooks, Microsoft Work/Office, Google Docs/Sheets, or other legacy information management systems and adopting new technology can be scary. There are a lot of unknowns: What do operations look like 3, 6, or 12 months after platform transition? And if you can’t visualise the end benefits for your organisation, then the project can seem like an unattainable fool’s errand, limiting acceptance and adoption.

Overcoming Fear of the Unknown

Bridging the gap between what is known on your current platform and what is unknown on the new platform is critical and can be accomplished with the help of a skilled vendor. In addition, evaluating the project's scope and laying out what barriers are expected over what timeframe can help define many of the unknowns in people’s heads. Team leads and those championing the transition process can further facilitate this approach by intertwining digitization tasks throughout daily, weekly, and monthly workflows so personnel can experience how the new platform works in a familiar context.

Reason for Resistance #5: Change in Daily Tasks

Old habits die hard, especially those that are an entrenched part of our daily routine. Learning a new technology is often viewed as a significant change in a company or lab that will disrupt familiar procedures that personnel have grown accustomed to.

Overcoming a Change in Daily Tasks

This resistance can be reframed as introducing a new tool that gets slowly integrated into daily tasks to elevate and improve them. You can think of your platform transition as introducing a new instrument that will increase a lab's analytical power and productivity.With an ELN, the benefits of features like automation and accessibility can serve as tangible examples of how daily tasks will change. You can demonstrate how the process of looking for specific biological samples will change: Previously, you’d open your freezer door and spend time shuffling through boxes, looking for samples and threatening their integrity as they heat up. With an ELN, you can show that a simple search in an inventory browser tab makes it easy to find the sample you need, minimising the time samples are exposed to the outside environment. Wherever you can, link the change in daily tasks to clear benefits, such as saving time and minimising the risk of sample degradation.

Reason for Resistance #6: Privacy and Security Concerns

For those in biotech and pharma, dealing with confidential information, patient data, and intellectual property, data security and privacy are very important issues. With a platform transition, new questions and concerns can arise about how secure it will be against data stealing and unauthorised access.

Overcoming Privacy and Security Concerns

Discuss vendor certifications and how they can facilitate regulatory compliance and data security. ISO certifications and compliance with GxP principles are essential in biotech and pharma.When choosing an ELN vendor, one thing to be careful of is seeing if a platform provider is ISO certified versus just their data centres. This gives you the best data protection and compliance with GxP principles.

Overcoming ELN Resistance with eLabNext

At eLabNext, we know there’s a lot of information to consider while evaluating which ELN fits your needs. We’ve provided a wide array of life science organisations, from small start-ups and academic labs to global corporations, with secure ELN software platforms that are flexible to fit the diverse needs of the industry.Here are some of how we can be your partner to overcome some of the internal barriers to digitization mentioned above:

• Comprehensive Onboarding: We take a standardised approach to onboarding, and within a 2 to 3-week period of working with our support team, your team will be largely up to speed on how to use eLabNext’s platforms. By the 4th week, your team will be confident in using the various functions of our system.

• Customer-Centric Support: Our support team is friendly, attentive, and informative so that you can get comfortable with our system and solve any problems that may arise. Each member of our team comes from a life science background, so they understand the intricacies of your questions and application areas.
• Best-in-Class Privacy and Security: Almost all vendors use ISO-certified AWS data centres, but the eLabNext company follows the strict requirements of the ISO/IEC 27001:2017+A11:2020 standard. This is a key differentiator with other ELN platforms for labs and facilities that need to comply with GxP and be audit-ready.

Now that you have read about these barriers and how to overcome them, you can have a digitization conversation with your lab or organisation. To help streamline this process and build a case for it, check out our series of white papers:

• White Paper 1: It's Time to Transition
• White Paper 2: Paths to Lab Nirvana
• White Paper 3: Evaluation Checklist

If you’re tired of reading and want to start testing eLabNext immediately, get a free 30-day trial or contact me directly for a personalised demo.

RNA-based therapeutics have been considered as a genuine ‘game-changer’ in the life sciences, a disruptive technology with almost limitless applications in both genetic and infectious disease. Initially slow to take off despite their potential, the successful deployment of RNA-based vaccines during the COVID-19 pandemic has helped to turn RNA-based therapeutics into a rapidly expanding category of drugs that could transform the standard of care for many diseases, helping to advance personalized medicine at the same time.‍

RNA molecules are cost-effective, relatively simple to manufacture, and can target previously ‘undruggable’ pathways. But that potential still requires streamlined workflows, efficient data-sharing and effective communications across states, countries, and continents. Laboratory digitization platforms have gained significant ground in recent years and are being adopted more widely alongside artificial intelligence (AI) and machine learning.

In this SelectScience^® article, we speak with Dr. Andre Serobian, Chief Innovation and Commercialization Officer at the University of New South Wales (UNSW) RNA Institute in Australia, and Lara Matthews, Business Development Manager at eLabNext, to understand the coming revolution in RNA-based therapeutics and the underpinning importance of lab digitization.

‍RNA-based therapeutics – a limitless future?

‍According to Matthews, the Australian biotechnology and life sciences industry is on a roll, experiencing a 43% growth since the COVID-19 pandemic first hit. RNA technology has been a major contributor to that growth, but it also includes new efforts in gene therapy and viral vector manufacturing. Working out of the UNSW RNA Institute, Serobian explains his excitement around RNA-based therapeutics, “This type of technology allows us to get into diseases that were previously untouchable, untargetable, or not treatable at all,” he says. “We can go down to and almost influence at a genetic level, especially for cancer, vaccines, and rare genetic disorders.”

Making an analogy with computing, Serobian describes RNA as the ‘software of life’ running on the DNA computer. He invites us to imagine a future in which diseases are cured directly by RNA technology and no longer tackled via symptom treatment, requiring only that the molecules are conceived correctly to make them effective. “RNA is a real game-changer in therapeutics,” he enthuses. “We’ll even go down the path – and there’s already work being done here – of neurodegenerative diseases such as Alzheimer’s, dementia and Parkinson’s disease,” he ventures.But Serobian and his colleagues at the UNSW RNA Institute understand that good science only takes you so far. In a frenetic world where data storage, data sharing, and effective communication is key, life science labs are increasingly adopting digitization to streamline their workflows and speed up therapeutics delivery.

‍Moving towards laboratory digitization

‍The UNSW RNA Institute has recently initiated the adoption of the digital laboratory platform from eLabNext, and remains in the process of developing the necessary systems. Serobian is convinced of the need to implement as much digital technology as possible, emphasizing the efficiency gains and how it provides technology transfer between different process levels, different groups, and across the institute’s network as a whole. Communication is key, as Serobian explains, “A digital platform like eLabNext just makes everything so much more efficient and so much better for information transfer, really communicating the essentials you need for progress and for a project not to lose momentum,” he asserts.Serobian describes a scenario in which a colleague is trying to find a sample or a particular hand-written entry in a notebook from six months ago, that was stored or recorded by a staff member who has since left the organization. This leads him to conclude that “it’s virtually impossible – digitization is crucial, and for any company that supports it and makes that part easier, I think the whole industry will benefit.”

‍COVID-19 – a driver of digitization

‍Serobian reflects in particular upon how he considers the COVID-19 pandemic to have been a proving ground for digitization, simply by dint of medical necessity. “When the virus was spreading all around the world, you had groups working frantically to create a vaccine,” he recalls. “It only became possible because of process and production efficiency and digitization of all that information. It created a critical path and would have been impossible otherwise,” he claims.According to Serobian, AI also contributed significantly to the COVID-19 vaccine effort, and he asserts that developing things quickly when times are critical can only happen when digital technologies are implemented. Matthews concurs, emphasizing “the collaboration aspect of being able to work on these advancements by transferring data quickly and seamlessly across the world.” She further adds, “You’re also saving so much money and time by not repeating failed experiments, for example. You can see where an experiment failed, make that information available to everyone so that no-one else repeats what didn’t work, and find a solution that works far quicker.”Matthews asserts that there is a ‘massive’ trend towards digital platform uptake in general, sometimes incorporating AI and machine learning, and that the Australian market has now seen its value in data use and sharing. She also indicates that eLabNext’s digital platforms have multiple AI plug-ins already that are freely available to their users.

‍What’s next for RNA-based therapeutics

‍Serobian offers an intriguing view of the future, “It’s really about tapping into disease states that we couldn’t tackle before, including infectious diseases, but it will also be used for wider applications of vaccines and to diagnose diseases,” he claims. “We’re going to see it being used as a platform or tool for all those areas. Everything can be tweaked in such a way to create a tool that is almost like a Swiss army knife, if you will,” he concludes.

Read on Select Science

To stay competitive, drug manufacturers are prepping for a future where algorithms control many elements of research and production.

The biopharma industry is rich with opportunities to boost productivity through automation, from computer-led drug discovery to fully validated vaccines rolling off production lines. But these kinds of innovations don’t spring from nowhere — they are underpinned by crucial layers of digital infrastructure in the lab. Tech-conservative firms hesitant to integrate digital tools and solutions such as electronic lab notebooks (ELNs), laboratory inventory management systems (LIMS) or laboratory information systems (LIS) risk being left at a competitive disadvantage when the AI revolution swings into high gear.

“Pharma companies are far behind many industries in terms of digitalization,” says Oliver Hesse, head of biotech data science and digitalization at Bayer Pharmaceuticals in Berkeley, California. “Partly that’s due to the unique challenges we face, but it also comes from being over-focused on avoiding risk or waiting for the proper use case. That’s a trap — you have to take a more holistic view.”With Hesse’s background in high-throughput screening, lab automation and data science, Bayer recently tapped him to manage a worldwide team charged with updating much of the company’s legacy equipment for the information age. The lessons he has learned about establishing seamless information transfer from process development to manufacturing could pay dividends to pharma firms looking to progress from digital record keeping to full-on automation.The value of structured dataWhile dealing with “systems that don’t play nicely together” has been the primary obstacle Hesse has faced, he notes that changing the mindset of researchers reluctant to adopt digital lab platform (DLP) tools such as ELNs and LIMS ranks a close second. To overcome this, Bayer dedicated a team of biotech engineers to work closely with laboratory users to put their needs at the forefront of a custom-built digital platform.“For the past two years, my focus has been to create an infrastructure that captures all of a user’s data, and to help people understand the value of structured data,” says Mehdi Saghafi, a biotech data engineer at Bayer with 20 years’ experience in process development. “After a lot of hand-holding, planning and strategizing, it's really starting to flower.”Saghafi explains that digitalization involves more than replacing paper lab notebooks with tablets, or simply dumping results into ever-expanding hard drives or one-dimensional digital tools. In a truly optimized digital lab, “the data no longer resides on a piece of equipment — it’s available at your fingertips.” The main challenge with implementing this vision, he notes, is finding people with the skill and creativity needed to modernize legacy equipment, workflows and databases using application programming interfaces (APIs).“Every instrument is different, and there’s no manual to tell you what to do,” says Saghafi. “It requires a certain amount of persistence, and many corporations aren’t willing to fund a group to manage the transition.”These sentiments are echoed by Zareh Zurabyan, head of eLabNext America, a DLP provider offering tools such as ELNs and LIMS from its base in Cambridge, Massachusetts. “It’s not like getting a centrifuge or a flow cytometer,” he says. “A digital solution like an ELN becomes the centrepiece of your daily routine. As well as unlocking research insights, having large-scale data at your fingertips will, at a minimum, influence your business strategy. We always recommend clients set up a committee to define what the digital strategy is from the outset.”

A holistic view

The ever-growing need to reduce time to market is driving pharmaceutical companies to adopt more efficient, data-oriented processing techniques. Central to that goal is managing data so it’s in the right place at the right time to learn from it. According to the Bayer team, taking a step back proved key to bringing disparate components together in an integrated infrastructure.“Look at the big picture — what is a bioreactor? A vessel with inputs and outputs. Now how do you control that, how do you fit that into a system?” asks Saghafi. “And think about handling the metadata around that bioreactor: things like the batch, the project, the operator. That’s where an ELN becomes crucial.”A typical process development setup has a hierarchical structure, with supervisory control and data acquisition (SCADA) software sitting at the top directing traffic between programmes such as a data historian and an ELN that acts as a user interface and a central hub for data analysis and process modelling. “There are lots of tools to transfer your lab analytical data, but if you can’t visualize and analyse them all in one place, they become meaningless,” states Saghafi.Zurabyan notes that eLabNext has open API and software development kits that allow just about any lab to push and pull data between instruments with ease. “It’s a modular system with fully indexed components, which makes it more intuitive to use,” he says. “Once you get used to it, you can keep adding more capabilities through our online marketplace, which features some of the top third-party AI tools in the industry. The idea is to build an innovation ecosystem to optimize research and process development.”The ability to find simple solutions for users proved key to driving adoption rates at Bayer. “Don’t overcomplicate things — that was a lesson for us,” recalls Hesse. “If you have 200 codes to memorize, it won’t flow with what you’re trying to do.”

The AI revolution is coming

Although the end user may not need to see it, a considerable amount of infrastructure needs to be in place for the digital lab to be successful. For Zurabyan, labs that make this investment will have a much greater chance of success when the next digital revolution hits. “AI is going to come out of nowhere and change everything,” he says. “When we consult with labs, we really focus on data standardization so it’s accessible to machine learning.”Saghafi likens these proactive efforts to communities paying taxes for new roads. “Sometimes we have to do uncomfortable things, but look — if you’re any good in the lab you already keep a notebook. Spend a bit of time with taxonomy, learn the proper way to capture and reference data with an ELN so that a person who has nothing to do with the lab can analyze it in its proper context.”Even with an expanded digital arsenal, innovation in the pharmaceutical industry still needs a human touch. “If implementation happens at the level of the end users and you partner with them to give them the right software, they take ownership of it,” says Saghafi. “The digital lab platform becomes the pillar of your innovation, capturing everything — your data, your repeatability, your future.”

Read on Nature

Digitizing your lab’s information can be transformative, improving your efficiency, data quality, and security. We’ve written extensively about how to make this transition, the benefits, and the key considerations for choosing one of the many open-source or commercially available software tools. In the life sciences, these tools go by different names: There are laboratory information management systems (LIMS), electronic laboratory notebooks (ELNs), environmental monitoring systems (for freezers and incubators), documentation management systems (DMS), electronic data capture (EDC) systems, equipment management software, sample labelling systems, electronic document management system (EDMS), electronic records management system, electronic lab management system (ELMS), laboratory record book (LRB), scientific data management system (SDMS), Molecular Biology Suites, chemical drawing software, and many others. These platforms each make distinct yet interrelated laboratory tasks easier. Depending on what you want your lab to do better, faster, or more cost-effective, you may use one or several of them to enable your transformative digital journey.

It’s Time to Evolve Beyond the “One-Trick Pony” Platform

But what if there was a flexible, multi-dimensional solution that could navigate every step of the journey with you? Grow with you as your operations grow and need change.At eLabNext, we’ve created a system that does just that, integrating all of the “one-trick pony” software tools mentioned above into a single, easy-to-use platform that can expand its functionality to fit your needs.We call it the Digital Lab Platform.

What is a Digital Lab Platform?

At the core of eLabNext’s Digital Lab Platform is an ELN, inventory and sample tracking system, and protocol manager, integrated for more efficient information storage and management. But what’s truly unique about eLabNext’s platform is our eLabMarketplace, where you can incorporate proprietary, modular Add-Ons. Think of it as the App Store on your iPhone, a central hub where you can customise how you perform laboratory tasks and manage information.The eLabMarketplace contains a library of available Add-Ons. We are constantly improving our collection, updating it with the latest and greatest life science applications for biobanking, productivity, reporting, and more. You also have the option to integrate any 3rd party software or build your own Add-On, giving your Digital Lab Platform nearly limitless ways to personalise your performance.

Benefit #1: Future-Proofed Operations

With the ability to expand functionality at will, your Digital Lab Platform is future-proof, poised for innovation and growth.This feature turns the disjointed digital tools we use daily into a cohesive unit: One Digital Lab Platform to govern all others. It also enables you to harness the powerful and ever-evolving world of computational life sciences. For example, we have recently introduced several AI-powered Add-Ons for image, single-cell, and multi-omics analysis to the eLabMarkeplace platform. Scientists no longer need to utilise multiple programs to grapple with challenging datasets but instead use one cohesive workflow within a single Digital Lab Platform.

Benefit #2: Comprehensive Data Security

Being the premier digital lab platform comes with great responsibility.That’s why we have an 8-fold replication of your data across multiple geographically dispersed data centres. Our fully redundant set of servers is fault-tolerant, so even in the rare event that a complete data centre blackout occurs, it won’t stop you from accessing our digital lab platform and your valuable data.

Benefit #3: API and SDK Technical Support

Even though our API and SDK are easy to use, our team of experienced developers is ready to help you get started. Our life science and IT experts are also more than happy to assist with brainstorming about your great product or services as part of the eLabNext Digital Lab Platform.

Experience a Better Path to Lab Digitization

Digital Lab Platforms can be the foundation of your company’s humble beginnings or a pillar of your global operations. We invite everyone from well-established companies to newly minted startups to implement eLabNext’s Digital Lab Platform and define a better digital strategy. Interested in seeing if eLabNext can serve your lab? Book a personal demo or start a 30-day trial today!

Genomics, proteomics, and other ‘omics technologies have delivered mountains of data and unprecedented insights to life scientists in academia, industry, and government. While powerful, these “big data” techniques have strained some outdated infrastructure, namely the paper lab notebook, for recording, storing, analysing, and distributing information in a laboratory setting.

Take genomics methods, for instance, which generate 10^21 bases per year in sequencing data and approximately 2 to 40 EB (that’s an exabyte; 1 quintillion or 10^18 bytes) per year that needs to be stored. This scale is beyond astronomical: If each byte were an inch long, it would stretch to the moon and back to Earth over 1 billion times. If you add on top of this the digital imaging data and other data-heavy techniques, the mass of data needs to be safe, secure, easily accessible, and sharable (as recommended by good scientific practices and mandated by many funding agencies) becomes overwhelming.

The Successes and Shortcomings of Paper Lab Notebooks

Despite heavy reliance on digital data, the nucleus for data, metadata, data analysis, protocols, and samples, is the paper lab notebook. Dependence on paper is a significant barrier to scientific progress. Paper and digital data don’t integrate seamlessly. Many researchers are forced into a hybrid existence that leads to data loss, issues with replicability and reproducibility, non-compliance with data-sharing mandates, and more. In fact, the NIH reported that problems with non-reproducibility stem from a lack of suitable documentation methods, many of which are associated with using a paper lab notebook.

So, Why are Paper Lab Notebooks Still Around?

Electronic Laboratory Notebooks (ELNs), which can offer a software solution for taking notes, data storage, and information organization, provide incredible advantages over paper lab notebooks.

Yet, many researchers enjoy the freedom of hand-drawing workflows or chemical structures, which can be done while wearing personal protective equipment (PPE). There’s also the need to learn a new software program, which can sometimes be complicated, mainly when it’s not intuitive to use and the user experience hasn’t been adequately considered. Ultimately, this leads to a low incentive to change their information management practices or adopt new ones.

3 Advantages of an Electronic Lab Notebook (ELN)

No doubt about it: Changing entrenched habits – even those that create inefficiencies and data loss – is hard.

However, the current data management challenges that many labs face are standing in the way of the scientific advancements enabled by big data.

ELNs offer an opportunity to improve the status quo, removing impermanent paper notebooks and insecure storage systems.

Reason to use an ELN #1: Promoting Reproducibility

Reproducibility has always been a significant issue in science. Yet, data collection and computation complexity is growing with the increasing reliance on big data, bioinformatics analysis, and many software tools. With it, the potential for additional issues with reproducibility increases.

ELNs offer a path towards better documentation of research workflows, revision tracking, and data management, helping other researchers repeat experiments in the future, preventing data loss, and enabling an efficient review process for all data.

Reason to use an ELN #2: Improved Accessibility

Ever tried flipping back through your old experiments or someone else’s to find a critical protocol or dataset? Paper lab notebooks make it notoriously difficult to locate historical records. It can be time-consuming to comb through older entries, even if there are user-constructed indexes or a table of contents.

The benefit of an ELN is that a user can quickly search protocols, entries, samples, or datasets using simple keyword queries, time ranges, metadata tags, or users. This also makes entries easy to re-order and sort, whereas, with a paper lab notebook, you’re locked into chronological ordering.

Reason #3: Instant Sharability

Collaboration and partnership are part of science; whether working with someone in the same bay or internationally, sharing critical information is necessary. With paper lab notebooks, sharing information with your colleagues is a time-intensive process that involves locating and scanning the applicable entries.

ELNs offer an attractive alternative, bringing Google Doc-like ease to sharing information. View/edit permissions can be granted instantaneously to entries, protocols, and datasets, regardless of geographical location.

Embrace the Advantages of Electronic Lab Notebooks

ELNs offer many other benefits that can transform laboratory operations and increase productivity.

Download the "Bringing ‘All Digital’ to Your Lab" whitepaper to learn:

• Drawbacks of using a hybrid information management system in the life sciences
• Why going “all digital” now will save you time and money in the long run
• More benefits to using an ELN for storing and tracking your life science data
• How eLabJournal can solve your paper lab notebook problems
• Why Deka Biosciences uses eLabJournal