Drug discovery

Miller, Susan M.; Moos, Walter H.; Munk, Barbara H.; Munk, Stephen A.

doi:10.1016/b978-0-08-100625-2.00010-6

Cited by 1 publication

(1 citation statement)

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“…Millions of molecules are tested, thousands are produced, and most fail to progress in preclinical or clinical settings (Shannon Decker and Atkinson, 2007;Mohs and Greig, 2017). Furthermore, translation from R&D to the clinic is insufficient with a success rate of less than 10%, and safety liabilities and poor efficacy cited as the main causes of attrition (Miller et al, 2017;Lowe, 2019).…”

Section: Introductionmentioning

confidence: 99%

Accelerating Therapeutics for Opportunities in Medicine: A Paradigm Shift in Drug Discovery

Hinkson¹,

Madej²,

Stahlberg³

2020

Front. Pharmacol.

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Conventional drug discovery is long and costly, and suffers from high attrition rates, often leaving patients with limited or expensive treatment options. Recognizing the overwhelming need to accelerate this process and increase success, the ATOM consortium was formed by government, industry, and academic partners in October 2017. ATOM applies a team science and open-source approach to foster a paradigm shift in drug discovery. ATOM is developing and validating a precompetitive, preclinical, small molecule drug discovery platform that simultaneously optimizes pharmacokinetics, toxicity, protein-ligand interactions, systems-level models, molecular design, and novel compound generation. To achieve this, the ATOM Modeling Pipeline (AMPL) has been developed to enable advanced and emerging machine learning (ML) approaches to build models from diverse historical drug discovery data. This modular pipeline has been designed to couple with a generative algorithm that optimizes multiple parameters necessary for drug discovery. ATOM's approach is to consider the full pharmacology and therapeutic window of the drug concurrently, through computationally-driven design, thereby reducing the number of molecules that are selected for experimental validation. Here, we discuss the role of collaborative efforts such as consortia and public-private partnerships in accelerating cross disciplinary innovation and the development of opensource tools for drug discovery.

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Section: Introductionmentioning

confidence: 99%