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Russell-Mazambara/GenRx

Domaine:

healthcare

Type de record:

software
Créateur:
Rus
HĂ´te:
AI-powered adverse drug reaction predictor for precision medicine in Southern Africa # 🧬 GenRx — AI-Powered Precision Drug Response Predictor > Adverse drug reactions kill an estimated 100,000+ patients annually. In Southern Africa, where over 17 million people across Zimbabwe, South Africa, Botswana, Namibia, Zambia and neighbouring countries are on antiretroviral therapy, personalized medicine is nearly inaccessible. GenRx uses machine learning, pharmacogenomics, and explainable AI to predict how individual patients respond to drugs — before they take them. --- ## The Problem Every drug prescription is a calculated risk. A clinician prescribes based on population-level averages — but patients are individuals. Their genetics, renal function, liver health, weight, and concurrent medications all influence how a drug behaves in their body. The consequences of getting it wrong are severe: - Adverse drug reactions (ADRs) are responsible for 100,000+ deaths annually in the US alone - Studies show that **up to 94% of ADRs go unreported globally** — meaning we are training models on incomplete ground truth - In Southern Africa, over **17 million people** across Zimbabwe, South Africa, Botswana, Namibia, and Zambia are on antiretroviral therapy — a population with uniquely high polypharmacy complexity and genetic diversity that most existing models ignore - The number of possible drug pair combinations runs into the millions, yet documented interaction data covers only a small fraction of those pairs The hardest problems in precision medicine are not ML problems. They are data problems, trust problems, and infrastructure problems. --- ## The Solution GenRx is a full-stack, production-oriented clinical decision support system that predicts: - **ADR risk score** per drug per patient, with confidence intervals - **Severity classification** — mild / moderate / severe / contraindicated - **Drug-drug interaction flags** with mechanistic explanations - **Plain-English clinical reasoning** powered by a knowledge-grounded LLM GenRx is designed …

Visit

github.com

Licenses

MIT

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<b>Spoken Hausa</b> . By J Ronayne Cowan and Russell G. Schuh. Ithaca, NY: Spoken Language Services, 1976. Pp. vi, 378.