Collaborative spirit helps drive innovation 

Dr David Walt, a professor at Harvard Medical School who runs labs at both Brigham and Women’s Hospital and the Wyss Institute at Harvard University, shares his thoughts on the drug discovery industry and what the pandemic has taught us about lab automation in the Winter issue of DDW Magazine’s accompanying exclusive DDW & SLAS2022 supplement .

Dr Walt’s lab has approximately 20 researchers, including postdoctoral fellows, graduate students, undergraduate students, and technical research assistants. He is also Co-Director of the Mass General Brigham Center for Covid Innovation, which spun up in the early days of the pandemic to help solve critical needs posed by Covid-19 for both patients and healthcare workers by facilitating innovative solutions. 

Discussing what excites him about his role, Walt says: “As an academic scientist, things are always changing. We make discoveries that lead us into new research areas. We are also immersed in an incredible clinical environment where we have the opportunity to engage with clinicians on important problems in healthcare. My lab develops new technologies to address unmet needs in clinical diagnostics and then applies them to cancer, neurodegenerative diseases, and infectious diseases.”  

Innovation in the current climate has been heavily influenced by the pandemic in many to most cases, across numerous industries. When asked if the pandemic has made his work harder or easier, Walt replies: “One of the most gratifying aspects I’ve observed is the tremendous amount of collaboration that occurred when Covid hit. Clinicians, researchers, engineers — everyone — did whatever they could to help solve the pressing problems that were appearing each day, as new information became available.  This collaborative spirit helped drive innovation. If we apply this kind of cooperation and collaboration to other pressing problems, we can help accelerate innovation and solve these problems.” 

Thinking about what the pandemic has taught us about lab automation, Walt says: “Laboratory automation was critical for helping scale up diagnostic testing. The demand for diagnostic tests for Covid-19 exceeded the entire capacity of the installed diagnostics laboratory testing base. The need for extensive sample handling and preparation prior to running PCR tests required a scale-up of testing in some labs to tens of thousands of samples per day. Laboratory automation was essential to meet the diagnostic testing capacity needed and this additional installed base will provide us with the ability to rapidly meet the needs for future testing. 

“In addition, laboratory automation has been critical to the discovery of therapeutics. There was – and still is  a need to find therapeutic interventions for Covid-19. The most effective and expeditious way to find these therapeutics is by repurposing already-approved drugs but there are many thousands of them that require screening. High-throughput screening requires sophisticated laboratory automation to test these molecules in biological assays.  The remarkable progress made to date in finding effective therapies stems from our ability to use laboratory automation throughout the discovery and validation process.” 

Drug discovery is always looking to be more efficient, faster, less costly as well as more successful. Asked how achievable this is and what the best ways to achieve it are, as well as what role lab automation and AI play in this, Walt says: “Lab automation and AI are the future of drug discovery. AI will be able to predict how therapeutics, including small molecules, antibodies, and nucleic acids, interact with and target the proteins or pathways implicated in the disease or condition. Fully automated systems will then be able to synthesise the requisite drug candidates and put them through biological screens to determine toxicity, efficacy, and perhaps even dosage. With the results from initial screens, the system will use an iterative process to refine and optimise the candidates, thereby down-selecting to provide a short list of molecules for further testing in human trials.” 

Walt sees the following challenges and opportunities in the global drug discovery and development sector now that we seem to be making some progress in tackling Covid-19: “While we will likely see some additional drugs come out of the repurposed drug screening effort, there is a tremendous amount of information now available about the virus—how it infects cells, what makes it more infectious, its pathogenesis. With recent advances in structural biology, we should be able to predict, design, and discover new drugs that specifically interfere with the pathways used by SARS-CoV-2 to infect and cause disease.” 

In way of prediction for the future of the industry, Walt comments: “For most of the ‘wet’ stuff — both for diagnostics and drug discovery — I predict there will not be much human involvement other than reviewing results and dealing with unexpected findings. Patient samples or drug candidates will be put through an intelligent and fully automated process, where initial screens will be used to identify the subsequent tests/workflows needed to further refine and validate an initial finding. The end result will be a patient diagnosis or a new drug lead with a full interpretable result generated by AI.” 

Volume 23, Issue 1 – Winter 2021/22 | SLAS2022 supplement 

Biography 

David Walt is Professor of Pathology at Harvard Medical School and Brigham and Women’s Hospital. He is the Hansjörg Wyss Professor of Bioinspired Engineering at Harvard Medical School and is a Core Faculty Member of the Wyss Institute at Harvard University.  Walt is Co-Director of the Mass General Brigham Center for Covid Innovation. He has received national and international awards and honours for his work in the field of optical microwell arrays and single molecules including the 2021 Kabiller Prize in Nanoscience and Nanomedicine, the 2017 American Chemical Society Kathryn C. Hach Award for Entrepreneurial Success and the 2016 Ralph Adams Award in Bioanalytical Chemistry. 

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