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Translating Molecular Science Innovations into Biotechnology Solutions Workshop

On May 14-15, 2024, UIDP convened more than 50 representatives from academic, government, industry, and nonprofit sectors to explore the translation potential of the currently funded teams of researchers in the Molecular Foundations for Biotechnology (MFB) initiative. MFB is a powerful collaboration between the National Science Foundation (four directorates with NSF-Chemistry [CHE] and NSF-Molecular and Cellular Biosciences [MCB] as the leads) and the National Institutes of Health (with the National Human Genome Research Institute [NHGRI] taking the lead).

Download the report for details about the workshop goals and findings. You may also download the presenter research award abstracts here.

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Multidisciplinary Research Areas for Further Exploration

The workshop’s goals were to explore the translation potential of the currently funded MFB work and identify frontier areas of research in the sphere of discovery science of paramount importance to the pharma/biotech industry and particularly well suited for the multidisciplinary research that the MFB collaborative initiative is well positioned to catalyze. The report identifies six areas for follow-on discussion:

  1. Innovations in Target Identification
  2. Innovations in Target Analysis/Dynamics
  3. Novel Modalities to Manipulate Biology
  4. Delivery
  5. Bioorthagonal Chemistry
  6. Big Data, Data-Sharing Repositories, Data Analytics, and AI and Machine Learning

Biomedical Long-Term Broader Impacts

Fundamentally new findings in the molecular sciences have the potential to vastly accelerate biotechnology development. With private sector co-investment and partnership in pursuit of mutually relevant research, federal agencies can identify funding priorities in areas with the most promise to yield high-reward results.

The leaders from pharmaceutical and biotechnology companies articulated several clear priorities in terms of challenge areas in biomedical science, specifically:

  1. neurodegenerative indications;
  2. cardiovascular health;
  3. oncology/cancer biology; and
  4. immune system-related indications.

Importantly, there was specific emphasis on more attention to women’s health care, an area that is historically under-resourced. This includes cancer, endometriosis, menopause/hormonal balance, birth and fertility, and post-partum depression.

High-level themes emerging from the workshop included the critical role of data (storage, analysis, and access), as well as tools and platforms that can leverage AI and machine learning to enhance discovery. Pooled data (perhaps using privacy-preserving encryption technologies) from both industry and academia is needed to create the training datasets to harvest the full potential of AI. Industry participants noted that this would require forming a consortium of companies and academics to power the data, similar to the PDB-enabled AlphaFold and other structure-prediction options. If enabled, AI and ML could specifically be applied to improve predictions of antibody-antigen interactions or protein-protein complex interactions.

 

 


This workshop was funded by the National Science Foundation through Award # 2419731