image: Leveraging 30+ validated PCC programs and over 12 years of model development experience to create a large-scale real-world “blind test” for frontier AI and foundation models, with a transparent public leaderboard.
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Credit: Insilico Medicine
As general-purpose and domain-specific AI models rapidly infiltrate drug discovery, one critical question looms over the pharmaceutical sector: Can these models actually discover drugs, or are they just good at taking tests? Today, most publicly available AI benchmarks suffer from severe data contamination, where models achieve artificially inflated scores simply by memorizing test questions present in their training data, only to fail when faced with real-world drug candidate decisions.
To close that gap, Insilico Medicine (“Insilico”, HKEX:3696), a clinical-stage generative artificial intelligence (AI)-driven drug discovery company, today announced the launch of the Drug Discovery and Development (DDD) Benchmarks as a Service (BaaS). It is a pioneering standardized evaluation framework anchored in carefully decontaminated real-world data and proprietary validated programs. for measuring how frontier AI and foundation models built on other architectures perform on real-world tasks across medicinal chemistry, chemical synthesis, disease biology, clinical development, and longevity research.
Insilico’s BaaS is available to any organization developing frontier AI for drug discovery or leveraging foundation models in their research. The DDD Benchmark provides an independent, real-world measure of how a model performs. The DDD Benchmark comprises two complementary evaluation suites:
Drug Discovery Foundations includes more than 300 evaluations built from proprietary out-of-distribution test sets and rigorously decontaminated public data. It measures a model’s core competencies across the discipline — spanning disease biology, molecular property prediction and optimization, retrosynthesis, structure-based design, and clinical development.
Drug Candidate Essentials evaluates a model’s ability to navigate an end-to-end drug discovery program, from hit identification through preclinical candidate (PCC) nomination. Its reference baselines are anchored in Insilico’s own validated programs, testing whether a model can make the sequential, high-stakes decisions that real drug discovery demands.
Benchmarking is straightforward: any model served through a standard chat-completions API can be evaluated by contacting Insilico Medicine. Insilico Medicine scores the resulting outputs against expert reference baselines and provides a standardized scorecard comparing performance with leading models.
Results are delivered with a verified score report that lets organizations certify performance for internal and partner audiences. Organizations seeking public recognition can also publish their results on the DDD Benchmark public leaderboard, giving the field a transparent, like-for-like view of model capability.
As AI systems increasingly act as agents (planning experiments, reasoning over experimental data, and calling MCP-compatible tools), the DDD Benchmark is designed to measure whether those capabilities translate into sound, real-world drug discovery decisions rather than strong performance on abstract tasks.
“The rapid progress of AI has made one question more urgent than ever: can these models actually discover drugs?” said Alex Zhavoronkov, Ph.D., founder and CEO of Insilico Medicine. “For more than a decade, we have built and validated generative AI across the entire drug discovery value chain, nominating 31 preclinical candidates in six years and advancing an AI-discovered and AI-designed medicine into Phase III. The DDD Benchmark converts that real-world experience into a rigorous, standardized yardstick that the whole field can use. As we advance toward pharmaceutical superintelligence, measuring genuine capability, not memorized answers, is how we ensure AI delivers the highest-quality, differentiated medicines and helps extend healthy, productive longevity for people everywhere.”
The DDD Benchmark builds on Insilico’s Pharma.AI platform and the MMAI Gym, the company’s post-training environment for scientific AI. Since its founding, Insilico has nominated 31 preclinical candidates, received over 10 investigational new drug (IND) clearances, and compressed the timeline to PCC nomination to roughly 12 to 18 months, compared with the 2.5 to 4-plus years typical of traditional drug discovery. Its lead program, Rentosertib (ISM001-055), is a first-in-class, AI-discovered and AI-designed TNIK inhibitor now in Phase III development for IPF.
The DDD Benchmark as a Service is available now. Organizations interested in evaluating a model, requesting a private assessment, or placing a model on the public leaderboard can learn more at dddbench.insilico.com.
About Insilico Medicine
Insilico Medicine is a pioneering global biotechnology company dedicated to integrating artificial intelligence and automation technologies to accelerate drug discovery, drive innovation in the life sciences, and extend healthy longevity to people on the planet. The company was listed on the Main Board of the Hong Kong Stock Exchange on December 30, 2025, under the stock code 03696.HK.
By integrating AI and automation technologies and deep in-house drug discovery capabilities, Insilico is delivering innovative drug solutions for unmet needs including fibrosis, oncology, immunology, pain, and obesity and metabolic disorders. Additionally, Insilico extends the reach of Pharma.AI across diverse industries, such as advanced materials, agriculture, nutritional products and veterinary medicine. For more information, please visit www.insilico.com.
Media Contact
Joy Hu
InSilico Medicine
Office: 475-225-0843
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/Applied sciences and engineering/Computer science/Artificial intelligence/Generative AI
