10 Years of Ardigen: Voices of Leadership Interview with Michał Warchoł, PhD, MBA
Q: When did you first realize that AI could truly transform the way we discover drugs?
Michał: I didn’t have one big “aha” moment about AI in drug discovery – it was more of a slow realization that grew between 2015 and 2020. During those years, a wave of new research showed that AI applied in drug discovery wasn’t just theory anymore- it could actually help scientists find new drug targets and design better drug candidates. That shift sparked a big change in the field, giving rise to “Tech Bio” companies that build their entire R&D process around AI-powered discovery. The story is still unfolding, but the real test will be when AI-designed drugs make it through clinical trials and onto the market-faster, cheaper, and with fewer failures.
Q: Which project has been the most challenging or exciting for you – and why?
Michał: One of the most exciting challenges I’ve faced has been a project that bridged chemistry and biology, focused on modeling how chemical structures (drug candidates) affect the morphology of various cell types. Our initial expertise was mainly in predicting the properties of small molecules from their chemical structures. Then we asked ourselves: what if we could also figure out how a compound works by looking at images representing cell morphology under perturbation? We enriched our structure-based approach with computer vision, fusing the two data modalities. This approach provides a clearer view of how drugs affect cells. That challenge pushed us to build our phenAID platform, engage in commercial collaborations, and join the JUMP-Cell Painting Consortium. What started as an experimental project has become a key part of what we do.
Q: What’s unique about Ardigen’s approach to AI?
Michał: What truly sets Ardigen’s approach to AI apart is the seamless fusion of deep domain expertise with advanced technology, creating a powerful engine for drug discovery. Instead of siloing knowledge, our teams of data scientists, bioinformaticians, software engineers, cheminformaticians and biologists work side-by-side from day one. This tight integration allows us to apply state-of-the-art machine learning algorithms to tackle the toughest industry bottlenecks by leveraging multimodal data integration. We process and harmonize diverse data types – from chemical structures and proteomics to cellular images – and use our combination of proprietary AI platforms and tailored services to transform this complex information into actionable insights you can actually use. It’s that blend of people, data, and tech that truly sets us apart.
Q: AI – how do you see its role now and in the next 5-10 years?
Michał: Currently, AI’s role as a powerful accelerator in early drug discovery is undeniable, even if its immediate impact is sometimes overestimated. It excels at sifting through vast biological and chemical data to speed up research, lower costs, and empower scientists by automating repetitive tasks, thereby creating space for innovation. In the next 5-10 years, I see AI evolving from this accelerator role into a genuine discovery engine that actively uncovers new biological targets and designs novel chemistry. This evolution will be transformative, enabling breakthroughs in previously intractable areas and significantly increasing the probability of success in drug development.
Q: How is technology currently influencing decision-making in pharma?
Michał: New technologies are significantly influencing how the pharmaceutical industry makes key decisions. Companies are now generating vast amounts of data more rapidly and cost-effectively, which provides the ideal foundation for advanced AI tools. The impact is felt at multiple levels within pharma (from research scientists to the management board) and at multiple stages of the drug discovery process (from target and hit identification to clinical trials). In particular, scientists are enabled to make more informed and efficient decisions, which holds the potential to significantly improve industry success rates.
Q: What excites you the most today as a technology leader?
Michał: AI is affecting the entire economy – some industries are changing fast, others more slowly. Life sciences, and drug discovery in particular, is one of the tougher areas. Evidence of change is slowly emerging, but it’s happening. I’m excited about how AI can help tackle one of humanity’s toughest challenges: getting the right drug to the right patient at the right time.
Q: What would you say to young scientists and engineers considering a career in AI for drug discovery?
Michał: For young scientists and engineers thinking about a career in AI for drug discovery, I’d highlight four key values that I believe make a difference. First, trust – working across different complex disciplines only works when people trust each other. Second, a commitment to lifelong learning, since this field is always evolving. Third, persistence – drug discovery is a marathon, not a sprint. And finally, keeping a strong focus on quality, always with patients in mind, so that the work we do actually leads to meaningful improvements in healthcare.
Q: How would you describe Ardigen’s tech DNA in one sentence?
Michał: Ardigen’s tech DNA lies in building bespoke discovery platforms by fusing our AI with deep biological expertise to solve our partners’ most critical R&D challenges.
Michał Warchoł, PhD, MBA Chief Technology Officer
