Phil Mounteney- VP of Science & Technology, Dotmatics
The New Normal
More than five years have passed since COVID-19 was declared a global pandemic, marking the beginning of a healthcare crisis that has claimed millions of lives and continues to shape our world today. Early efforts to contain the elusive and ever-evolving SARS-CoV-2 virus demanded unprecedented collaboration among nations, healthcare systems, and industry innovators. The pandemic stands as a defining moment in history - not only for its profound toll on human life, but also for how it fundamentally reshaped the landscape of modern drug discovery.
The “new normal” - an expression so often heard back in the throes of the crisis - now necessitates deeper collaboration and strategic use of AI, data, and automation to deliver rapid innovation. Today, preparing for future public health emergencies and furthering progress against other hard-to-treat diseases are driven by agility, flexibility, and collaboration. These are the same key tenets that were paramount to the world’s pandemic response.
What specifically has changed in the realm of drug discovery?
Principles of Post-Pandemic R&D
COVID-19 disrupted traditional R&D paradigms, compelling research teams to become more agile, flexible, and collaborative. Saving lives meant shattering traditional timelines, sharing data for the greater good, and leveraging established knowledge to rapidly deliver breakthroughs.
Open Data
During the pandemic, we witnessed an unprecedented level of open-source work, with data about the virus and potential treatments widely shared in hopes of speeding up drug discovery. COVID Moonshot, for example, saw cross-disciplinary scientists worldwide collaborating on the development of antiviral candidates. The distributed computing initiative, Folding@home, enabled those researchers to band together their computing resources to power simulations to study proteins and drug targets. Project Discovery enlisted the help of online gamers to analyze huge volumes of flow cytometry results data, not only helping researchers better understand how the human immune system responds to COVID-19, but also letting them collect training data for AI models.
These collaborative scientific initiatives have continued to gain traction in the post-pandemic era. In late 2024, Google DeepMind’s AlphaFold 3, an AI program for predicting protein structures, was made open source to academic researchers. This will help researchers more quickly grow their understanding of biological targets and potential drug candidates.
AI-Aided R&D
Building upon established knowledge and leveraging advanced technologies, particularly AI, was key to quickly delivering COVID-19 breakthroughs. For example, AI-based protein modeling helped researchers quickly identify treatment targets, and machine learning was used to accelerate clinical trial data analysis.
Following COVID-19, innovators are increasingly looking for ways to strategically integrate AI into their R&D workflows in order to reduce timelines and manage costs across the board. Today, AI applications include modeling proteins and molecular interactions, optimizing new drug candidates, and guiding drug repurposing initiatives.
Adaptive Accelerated Trials
Departing from conventional clinical trial design proved essential when evaluating urgently needed vaccine candidates during the pandemic. Accelerated trial phases and adaptive designs with interim analysis enabled researchers to quickly identify effective interventions. Post-pandemic, adaptive trial design software has gained recognition as an innovative and effective tool for designing clinical trials, particularly for therapeutics targeting complex conditions such as cancer, Ebola, Alzheimer’s disease, and other challenging medical conditions.
Non-Traditional Modalities
Researchers embraced nontraditional vaccine development, pursuing mRNA vaccines by leveraging existing mRNA platforms. The rapid vaccine turnaround comes on the coattails of platforms that were developed over 20 years. The distinctive value of these platforms lies in their flexibility and adaptability. Researchers were able to build off decades of work on mRNA vaccines and quickly adapt solutions for COVID-19.
This success has stimulated broader interest in mRNA vaccine applications, such as for personalized immunotherapy, as well as other alternative vaccine platforms, such as those based on adenovirus vectors and DNA Mabs, which aim to serve as flexible immunization options for conditions such as influenza, Ebola, HIV, malaria, and more.
These efforts reflect an even larger research trend of embracing flexibility within the world of drug discovery, most notably via a multimodal approach to R&D. Innovators are looking to flexibly address hard-to-reach targets through the best means possible, whether that be small molecules, biologics, or conjugates. Biotech companies are responding with new R&D tools to support this growing need for research diversity and flexibility.
Public-Private Collaboration
A critical lesson from the pandemic was that expanded cooperation across pharma, biotech, and government agencies is needed to tackle global health challenges. ACTIV exemplified this ideal. Spearheaded by the US National Institutes of Health (NIH), ACTIV, or Accelerating COVID-19 Therapeutic Interventions and Vaccines, was a public-private collaboration that aimed to accelerate the development of COVID-19 vaccines and treatments by aligning goals and sharing resources.
Those efforts continue today to prepare for future pandemics. The Research and Development of Vaccines and Monoclonal Antibodies for Pandemic Preparedness Network (ReVAMPP) is bringing together researchers, public health officials, and pharmaceutical companies to explore the adaptability of mRNA and monoclonal antibody technologies for other high-priority virus families.
These types of collaborative efforts aren’t limited to pandemic preparedness. For example, OneHealthTrust is leading a number of initiatives to tackle another global health threat: antimicrobial resistance. And, in the area of oncology, Partnership for Accelerating Cancer Therapies (PACT) is bringing together public and private organizations to help advance immune cancer therapies.
Elevating the New Normal Through R&D
“Amid every crisis lies great opportunity,” was often quoted by Albert Einstein. This remains true in today’s R&D landscape. While the pandemic undeniably caused significant hardship and loss worldwide, we can now begin to appreciate the opportunities that emerged in its aftermath.
Beyond advancing scientific boundaries, COVID-19 also transformed research methodologies. The ability to deliver life-saving therapeutics to patients more rapidly and affordably, and rreducedevelopment costs from billions to millions of dollars is a longstanding goal in drug discovery. In the post-pandemic research landscape, AI-driven tools, automation, cloud-based collaboration, and multimodal discovery approaches have become fundamental to R&D, making the process faster, more efficient, and more cost-effective.
Author Biography
Phil Mounteney is the Vice President of Science & Technology at Dotmatics, a provider of R&D scientific software that connects science, data, and decision-making. Phil has worked in a variety of leadership roles at Dotmatics since 2009.
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