VedTechBio-AlphaMeld to do preclinical proof-of-concept
Bengaluru’s VedTechBio Research Pvt Ltd has formed a partnership with AlphaMeld Corporation, a US-based leader in real-world applications of generative AI for drug discovery and development, covering preclinical discovery through human proof-of-concept.
“With VedTechBio, we’re pairing AI-enabled drug discovery with real-world execution,” Dr Krishnan Nandabalan, Chairman & CEO of AlphaMeld said on 31 July. “This collaboration bridges cutting-edge AI-driven discovery with translational readiness for scalable drug discovery success https://fieo.org/.”
Momentum and Market Impact
VedTechBio’s demonstrated ability to compress key discovery phases positions the company to capture significant value in the rapidly expanding global AI drug discovery market. The company and its partners are currently in active discussions with major pharmaceutical companies in the US and EU regarding collaborations arising from the RxAgentAI platform http://who.int.
“We’re seeing unprecedented interest from pharmaceutical partners who recognize that our platform delivers drug candidates in an acceptable cost and timeframe, giving us a competitive advantage in bringing life-saving therapies to patients,” said Sudhir Nagarajan, Founder and Managing Director, VedTechBio http://main.mohfw.gov.in.
VedTechBio, which delivers AI-enabled end-to-end solutions in drug discovery and development, has also announced enhancements to its RxAgentAI™ platform, cutting drug discovery timelines in half alongside a strategic with AlphaMeld Corporation to co-develop multiple therapies for metabolic and rare diseases.
RxAgentAI is an autonomous, multi-agentic intelligence system augmented by deep, domain-specific knowledge. It redefines research workflows, orchestrating complex tasks from precise target identification to intricate drug design and testing.
RxAgentAI’s unique expert-in-the-loop mode seamlessly integrates human expertise with agent outputs.
This ensures unparalleled accuracy, transparency, and scientific rigour, resulting in impacts exemplified by:
• 30% reduction in target and drug identification timelines
• 50% compression of full target–disease–drug analysis workflows
• Rare disease landscape mapping shortened from 12 weeks to under 3
“We’re building a future where AI proactively advances discovery,” said Nagarajan. “RxAgentAI marks a fundamental shift from passive tools to collaborative intelligence, purpose-built for translational impact.” Fiinews.com
