Evidence map›Paper›PMID 42679153›Full record

ArticleJournal of medicinal chemistry2026

Bridging the AI Divide in Drug Discovery: Practical Lessons from Capacity Strengthening in Africa.

Jason Hlozek, Miquel Duran-Frigola, Nicola Elliott-Wong, Rudolf Stander, Susan Winks, Gemma Turon, Kelly Chibale

Abstract read
In one paragraph

Article in Journal of medicinal chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jason HlozekHolistic Drug Discovery and Development (H3D) Centre, University of Cape Town, Cape Town, Western Cape7700, South Africa.
Miquel Duran-FrigolaErsilia Open Source Initiative , Barcelona08039, Spain.ORCID 0000-0002-9906-6936
Nicola Elliott-WongH3D Foundation, Cape Town, Western Cape7700, South Africa.
Rudolf StanderH3D Foundation, Cape Town, Western Cape7700, South Africa.
Susan WinksHolistic Drug Discovery and Development (H3D) Centre, University of Cape Town, Cape Town, Western Cape7700, South Africa.ORCID 0009-0001-3639-5572
Gemma TuronErsilia Open Source Initiative , Barcelona08039, Spain.ORCID 0000-0001-6798-0275
Kelly ChibaleHolistic Drug Discovery and Development (H3D) Centre, University of Cape Town, Cape Town, Western Cape7700, South Africa.ORCID 0000-0002-1327-4727

Funding

European Commission PID2023-148309OA-I00Ministerio de Ciencia, Innovaci??n y Universidades PID2023-148309OA-I00Schmidt Sciences G-23-65555
6 · The paper itself

Abstract

Artificial Intelligence (AI) has become an integral part of drug discovery in high-income countries. However, these advances have yet to be broadly adopted by research ecosystems in many low- and middle-income countries in Africa, where understudied infectious diseases, compounded by a growing noncommunicable disease burden, cause millions of deaths each year. Given adequate support and appropriate models AI could play a transformative role in under-resourced biomedical research ecosystems in Africa, democratizing drug discovery research. There is an urgent need to invest in building the critical infrastructure, tools, and capacity required. To drive this agenda forward, Ersilia, the H3D Centre, and H3D Foundation with support from the AI2050 program at Schmidt Sciences hosted a series of in-person and online workshops in Africa to grow the AI skills base for medicinal chemistry and enable adoption across regional research hubs. In this perspective article, we discuss the lessons learnt from this program, the fit-for-purpose open-source tools developed, and key considerations for future initiatives.

Indexed as

Artificial IntelligenceDrug DiscoveryAfricaHumans

Identifiers

PMID42679153
PMCPMC13528195

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.