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NOBEL PRIZE 2026

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NIHNATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCESR25

Continuing Education for Structural Biology Mentors

Active
Institution
HARVARD MEDICAL SCHOOL, MA
Principal investigator
Piotr Sliz
Funding
$451K
Duration
2023–2028
Open portfolio

Moonbase score

Still being scored

Abstract

The structural biology and molecular modeling market is expected to reach USD 18.1 billion with a Compound Annual Growth Rate (CAGR) of 17.1% during the forecast period of 2022-2028, which has the potential to drive substantial demand for a workforce of the future. While the significance of advancement in cutting-edge Cryo-EM data processing to improve and accelerate drug discovery to treat diseases is driving innovation and economic growth and happening in the pharma industry, many structural biology investigators and would-be investigators are caught without the enhanced research training to use rapidly evolving and sophisticated computational tools, including AI and deep learning tools, proficiently to help the pharma industry accelerate drug discovery for society. In particular, the high costs associated with Cryo-EM research present a significant barrier for less-resourced institutions to train their students for the structural biology-based biomedical career of the future. To address these challenges, the Structural Biology Grid (SBGrid) Consortium at Harvard Medical School and Belmont University will continue their existing partnership to deliver an enhanced research training program for structural biology investigators on the current Cryo-EM and Cryo-ET data processing workflow that includes AI components, necessary skills, knowledge, and best practices to help them stay on top and be productive in their careers in the biomedical research workforce. Additionally, the program is designed not just to impart training for the principal investigator participants but also to increase sustainability and scalability by enabling them with an evidence-based, integrated data science training model and system for structural biology comprising a complete set of training program material with training datasets, a collection of structural biology data analysis and visualization software, and a sustainable training and computing environment with supporting resources that they could use in their home institutions to provide continuing education and longitudinal mentoring to their laboratory members and students who are pursuing next-generation biomedical careers in structural biology.

Research team

  • Jamaine S DavisPI
  • Piotr SlizPI

LOADING MOONBASE SCORE

R25NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCESZGM1-TWD-Z(IP)biologystructuraldrug discoverystructural biologydata processingcryo-emcontinuing educationcontinuing

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