Almost 90% of drug candidates fail in clinical trials, and nearly half of those failures occur to blind spots around Absorption, Distribution, Metabolism, Excretion, and Toxicity properties.
An AI-powered solution from Edmonton’s Proholistic Discovery aims to empower researchers to make data-informed decisions earlier in the process.
“With deep expertise spanning target identification, lead optimization, and clinical development, we provide science-driven, quantitative insights that enhance decision-making, reduce risk, and improve overall program success,” the startup states online.
The technology from Proholistic Discovery combines systems thinking with inference-driven AI for Pharmacokinetics, Pharmacodynamics, and Systems Pharmacology modelling to guide smarter drug discovery.
The Canadian upstart was founded in 2024 by theoretical physicist Richard Tseng alongside Jack Tuszynski, a longtime University of Alberta professor of physics and oncology.
With over 15 years of experience across computational biology and preclinical drug development, Tseng applies information theory, AI, and mechanistic PK/PD modeling to uncover patterns that make drug discovery faster, smarter, and more predictable.
He says that Proholistic’s platform does not attempt to replace existing tools.
Rather, “It revolves the uncertainty by turning incomplete, fragmented predictions into actionable insights that better reflects human biology,” Tseng informed Life Sciences Review earlier this year.
Proholistic, an Edmonton 50 company, claims its “cutting-edge, proprietary technology” and AI-driven approach can design highly specific RNA/DNA aptamers for any biomolecular target in just two weeks.
“This breakthrough accelerates discovery and development, saving both time and resources,” the company states.
Proholistic, which collaborates with Applied Pharmaceutical Innovation and serves as a resource for Innovate Calgary’s Expert Advisory Program, was recently named one of 10 companies to watch by Edmonton Unlimited ahead of this year’s Startup Week in October.
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