Competitors agree to a standard, Pistoia Alliance predictions, New era of the lab, GEN Interview with our CEO, Breaking down silos, Virtual clinical trials, Semantic tech, Trust in leadership, Data as a priority
Your Predictions for the 2020s
From Fortune CEO Daily Newsletter
TetraScience Take: We 100% agree with Doug Merritt's prediction. Organizations now capture and store more data than most can fathom, but the vast majority of it goes wasted. That's why we are on a mission to activate the flow of data for our life sciences R&D customers.
Excerpt: "Lots of good responses to my request for predictions for the next decade, with two issues predominating—the rapid advance of data and A.I., and the rapid deterioration of skills as a result..." Read all the quotes
Roche and Fortelinea to co-market software solutions in US to improve workflow in histology research labs
TetraScience Take: This partnership between Roche and Fortelinea demonstrates the current point-to-point thinking towards improving lab workflows. This market is too fragmented. To truly create a connected lab, we need a vendor-neutral solution.
Excerpt: "The agreement enables U.S. labs with Prima software and Roche's DISCOVERY ULTRA automated IHC/ISH staining system with VENTANA Connect middleware to utilize one barcode across both platforms, allowing standardized slide labeling and streamlining data transfer and integration with the laboratory information system. The resulting automated IHC and ISH workflows help reduce turnaround time, redundant work and manual errors, improving the overall efficiency of lab processes..." Press release
In a rare move, Apple, Amazon, and Google just announced a major partnership
From Business Insider
TetraScience Take: As a supporter and member of the Allotrope Foundation, a consortium of large pharmaceutical companies that are driving standardization amongst analytical data, we applaud this collaboration among Apple, Amazon, and Google to adhere to a smart-home device connectivity standard that will ultimately benefit the end users (all of us!). Of course this is a less complicated task in a market dominated by a few top players. But still, it is an effort to be celebrated, and an example that it can be done.
Excerpt: "Three of the world's biggest tech companies — Apple, Amazon, and Google — are putting aside years of competition and creating a joint technology standard.
The new standard is aimed at smart-home products like Amazon's Echo, Apple's HomePod, and Google's Home. It's called "Project Connected Home Over IP," a very specific name for a group with a very specific goal: "To develop and promote the adoption of a new, royalty-free connectivity standard to increase compatibility among smart home products, with security as a fundamental design tenet," the companies announced on Wednesday [December 18].
More simply put, the group aims to create a single standard used by all creators of smart-home products.
That single standard, the group said, would "simplify development for manufacturers and increase compatibility for consumers..." Full story
TetraScience Take: Predictions abound this time of year. Here's an interesting one about life sciences and health by the Pistoia Alliance told as a retrospective from 2030. Spoiler alert - technologies include AI/ML, blockchain, cloud computing, quantum computing, medical devices, digital – including biomarkers, diagnostics, monitoring and therapeutics, internet of things (IoT), laboratory automation, tissue and organ regeneration, liquid next generation sequencing, therapeutic molecule synthesis.
Excerpt: "The not-for-profit organisation’s ‘2030: Life sciences and Health in the Digital Age’ report imagines what the next 10 years of technological, social and political evolution will be like in relation to pharma and life sciences.
The report mentions that by the early 2020s, AI will be largely responsible for diagnosing patients – resulting in healthcare providers suffering from a serious shortage of physicians. However, the report warns that widespread deployment of automated diagnosis will result in patient deaths, caused by algorithms making errors. Drug discovery will see transformation due to pharma companies using advanced algorithms and modelling to design innovative drugs of high specificity and low toxicity..." Full story
The New Era of the Laboratory
From American Laboratory
TetraScience Take: We couldn't have defined the data challenges in the life sciences lab better ourselves - too much manual effort, low confidence in data quality, difficulty in digitally transforming legacy instruments, and lots of data wasted. As the article says, "Driving innovation through good decisions is paramount, and this link in the workflow between capturing and analyzing data is as much about enabling innovation as it is about lab efficiency." - Rob Brown, VP Product Marketing, Dotmatics. Glad to have Dotmatics as a strategic partner to help tackle these challenges to advance towards the Digital Lab of the Future.
Excerpt: "It’s no secret that data is the new oil – but the ultimate value for a life sciences company comes only when it can turn its data into knowledge that drives decision making. The ability to gather data from lab equipment, via the Internet of Lab Things (IoLT) and software solutions, enables researchers to simply access complete and accurate data from lab equipment. But as data volumes grow and complexity deepens, it is outgrowing the traditional means of collecting that have been used before – such as, file transfers, and even manual collection and curation. These approaches are no longer practical and are contributing to the current laboratory productivity crisis. With new IoLT devices capturing data, labs now need to ensure they have comprehensive solutions in place to take data and seamlessly connect it to decision support software.
To do this successfully, companies need a solution at the end of the chain that not only captures and interprets experimental results but harmonizes and serves data up to either project scientists and/or to AI tools to allow analysis to take place..."Full story
Looking Towards the Digital Lab: An Interview with TetraScience’s CEO
From Genetic Engineering & Biotechnology News (GEN)
TetraScience Take: Great interview with TetraScience's own Spin Wang about the importance of and challenges with data in the bioprocess 4.0 digital lab of the future.
Excerpt: "GEN: Why is data management important? Wang: Data management is the backbone of analysis. Because bioprocessing is an end-to-end process, like growing or cooking something, you’re constantly monitoring parameters like the optimum conditions to grow your cells. With analytics, you can feed that data back into an algorithm, which can help you make plans or adjust parameters in real-time." Full interview
Harvard, MIT, and GE to collaborate on unique biotech center
From Boston Business Journal
TetraScience Take: Silos cause major pain points. At TetraScience, we focus on breaking down data silos. This new collaboration of Harvard University, MIT, Fujifilm Diosyn Biotechnologies, GE Healthcare Life Sciences, and Alexandria Real Estate Equities breaks down functional silos to reduce the amount of time from discovery to clinical application.
Excerpt: "A powerful consortium of some of the world’s most recognized names in higher education, health care, real estate and life sciences is collaborating to create a center for advanced biological innovation and manufacturing.
The $50 million first-of-its-kind center, which will be set up as an independent nonprofit, will explore regenerative therapies in a cross-sector environment that aims to shorten the gap between research, biomanufacturing and clinical application..." Full story
Janssen drops clinical sites for smartphones, wearables in 100% virtual Invokana study
TetraScience Take: Clinical trials are slow, expensive, and biased. Celebrating
Janssen's first virtual clinical trial! Physical activity data is tracked automatically by a wearable; participants can access their data.
Excerpt: "Johnson & Johnson’s pharmaceutical arm Janssen is launching its first completely virtual clinical trial, using personal smartphones and wearable devices to track participants with no in-person site visits required..." Full story
Is semantic technology the AI sweet spot for pharma?
From European Pharmaceutical Manufacturer
TetraScience Take: Semantic web is the next AI term you need to know. It removes biopharma research bottlenecks around data identification, extraction, quality, harmonization, integration....and it is available today.
Excerpt: "Artificial intelligence (AI) has been trumpeted by many in the pharmaceutical industry as the magic bullet to the issues they face in drug discovery and other research. However, expectations need to be tempered because although it’s easy to get excited by the potential of AI it’s important not to get too carried away with the reality of what’s possible today – at least at low cost and at virtually no risk.
The standout value that AI can currently provide to the pharmaceutical industry is in removing the bottlenecks around data identification, extraction, quality, harmonisation and integration. These are all issues that have plagued the pharmaceutical industry for a long time. And in an age of digitisation where researchers are increasingly facing a proliferation in the types and variations of data, including drug doses and molecular structures in many forms, such as text, numbers and images; it’s AI that can play a vital role in helping to make sense of it all..." Full story
[Report] Build Your Trust Advantage: Leadership in the era of data and AI everywhere
From IBM Global C-suite Study, 20th Edition
TetraScience Take: Businesses are generating and collecting vast amounts of data. According to this study, only 9% are generating real value from that data. The keys are trust, collaboration, leadership buy-in, and revenue goals.
Excerpt: "Data, coupled with advanced analytics and AI, including machine learning, can inform superior enterprise decisions and optimize and automate processes—but only if organizations can deeply trust their data. To do so, organizations are learning to master the quality of data, mitigate algorithmic bias, and serve up answers with evidence..." Summary and download
Using AI to Understand What Causes Diseases
From Harvard Business Review
TetraScience Take: We all know that AI will transform how we understand and treat diseases, and as this article says, "data is key"! But collecting the data is challenging. We know - it's what we do all day every day.
Excerpt: "Health care leaders are embracing AI. But by conducting an extensive review of case studies and research literature, we’ve found that their AI initiatives are predominantly focused on developing algorithms that can predict a problem such as cancer in order to make diagnoses better, faster, and less expensively. Rarely, are their organizations devoting resources to AI efforts aimed at understanding why diseases occur. To intervene as effectively as possible, both kinds of algorithms are crucial..." Full story
TetraScience Take: BigData, Cybersecurity, and Blockchain are all super important. But don't forget the important, sometimes dirty, work to collect the data in the first place.
Excerpt: "GlobalData’s latest report, ‘Emerging Technology Trends Survey – Pharma 2019’, reveals that over 70% of pharma executives, who have some level of responsibility with regards to the implementation of new and emerging technologies, prioritize data protection and storage solutions for their investments..." Full story
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