# Lead optimization of hits identified from virtual and experimental screens of multiple industrial libraries DNDi > **NIH NIH R33** · NORTHEASTERN UNIVERSITY · 2021 · $433,246 ## Abstract SUMMARY/ABSTRACT Neglected tropical diseases (NTDs) are a leading cause of morbidity and mortality, affecting over 1 billion people worldwide. Given the lack of financial incentive for the for-profit pharmaceutical industry, there is little translation seen from in vitro drug screening assays into in vivo efficacy studies. We propose to progress hit compounds, identified from pharmaceutical company compound libraries, through to pre-clinical candidate status. To achieve this, we have engaged with the Drugs for Neglected Diseases Initiative (DNDi), effectively aligning ourselves with several partners who bring deep expertise from industry, in medicinal chemistry, drug metabolism and pharmacokinetics, and from institutions that contribute parasitology experience and a proven ability to progress drugs for NTDs into the clinic and beyond. Such a project team is singular across the NTD drug discovery landscape and is a strength of this proposal. We will accomplish the proposed project goals by focusing our attention on the design of compounds which meet the Target Product Profile (TPP) for visceral leishmaniasis and Chagas disease. DNDi's Booster program identifies starting hits through a unique process, involving iterative screening and testing cycles of 7 pharmaceutical company compound libraries. The compound members of each library are well annotated with known pharmacological activity, and computationally predicted and/or experimentally measured properties (including aqueous solubility, metabolic stability, in vitro toxicology etc.), enabling the rapid identification of potential liabilities. This proposal focuses on four chemotypes that emerged from the Booster program that consist of a large number of validated hits against Leishmania spp. and Trypanosoma cruzi. The R21 phase will be focused on hit-to-lead optimization and the down-selection of the four chemotypes to two. We will identify compounds that demonstrate proof-of-concept disease-modifying effects in animal models of the respective diseases. Further, we will profile those compounds that demonstrate positive effects on parasitemia in vivo to identify potential liabilities, which will become the focus of the candidate-seeking medicinal chemistry campaign outlined in the R33 phase. The R33 phase is focused on the lead-to-preclinical candidate optimization of the prioritized chemotypes. We are uniquely placed to achieve this goal as we are collaborating directly with DNDi and Celgene Corporation throughout this project. At the completion of the R33 phase we will deliver a complete data package on two compounds for each disease (one candidate, one backup) that meets the respective TPP, and which will be used to justify IND-enabling studies. ## Key facts - **NIH application ID:** 10320259 - **Project number:** 4R33AI141227-03 - **Recipient organization:** NORTHEASTERN UNIVERSITY - **Principal Investigator:** MICHAEL P POLLASTRI - **Activity code:** R33 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $433,246 - **Award type:** 4N - **Project period:** 2019-02-22 → 2024-01-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10320259 ## Citation > US National Institutes of Health, RePORTER application 10320259, Lead optimization of hits identified from virtual and experimental screens of multiple industrial libraries DNDi (4R33AI141227-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10320259. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*