About us
What is Inventum.AI?
Represents a transformative advancement in therapeutic discovery, reshaping pharmaceutical research with enhanced efficiency and precision. By integrating the expertise of its multidisciplinary team with state-of-the-art Generative AI technologies, the Inventum.AI platform improves the accuracy of drug molecule design. Additionally, it democratizes drug discovery, empowering a broader range of organizations to contribute to the development of innovative treatments.
Leadership Team
Education
- • 2012 PhD (Candidate of science).
- • 2010 Masters degree. Kazan State University, Department of Economical cybernetics.
- • 2007 Bachelors degree, with honors. Kazan State University, Department of Calculation Mathematics and Cybernetics.
Experience
- 2021–2023: Founded and led the AI Institute at Innopolis University, directing a team to complete 50+ projects with revenues > $20 mln.
- 2020: Developed an AI radiology service for chest X-rays with Moscow’s Health Department, earning $1M revenue.
- 2008: Founded Pulmoscreen, a radiology software startup, with installations in over 10 hospitals.
- Published >20 scientific publications in peer-reviewed, top-tier, peer-reviewed journals (h-index is 8, Google Scholar account).
Education
- • 2012 PhD (Candidate of science).
- • 2010 Masters degree. Kazan State University, Department of Economical cybernetics.
- • 2007 Bachelors degree, with honors. Kazan State University, Department of Calculation Mathematics and Cybernetics.
Experience
- 2021–2023: Founded and led the AI Institute at Innopolis University, directing a team to complete 50+ projects with revenues > $20 mln.
- 2020: Developed an AI radiology service for chest X-rays with Moscow’s Health Department, earning $1M revenue.
- 2008: Founded Pulmoscreen, a radiology software startup, with installations in over 10 hospitals.
- Published >20 scientific publications in peer-reviewed, top-tier, peer-reviewed journals (h-index is 8, Google Scholar account).
Education
- • 2019-2023 PhD Candidate in Physical chemistry.
- • 2019 Specialist degree, Kazan State University, Chemistry Institute.
Experience
- 2018: Founded Octium, focusing on the development and production of novel catalytic systems for silicones.
- 2020–2023: Principal Investigator at the AI in Materials Lab, Innopolis University, leading successful collaborations with research groups from Switzerland, Singapore, and Norway. Achieved 2nd place in the Open Catalyst 2021 Challenge by Meta AI with a proposed Graph Neural Network solution.
Authored >15 publications, including papers in top-tier journals such as Nature Communications, and holds 5 patents.
Authored >15 publications, including papers in top-tier journals such as Nature Communications, and holds 5 patents.
Education
- • 2019-2023 PhD Candidate in Physical chemistry.
- • 2019 Specialist degree, Kazan State University, Chemistry Institute.
Experience
- 2018: Founded Octium, focusing on the development and production of novel catalytic systems for silicones.
- 2020–2023: Principal Investigator at the AI in Materials Lab, Innopolis University, leading successful collaborations with research groups from Switzerland, Singapore, and Norway. Achieved 2nd place in the Open Catalyst 2021 Challenge by Meta AI with a proposed Graph Neural Network solution.
Authored >15 publications, including papers in top-tier journals such as Nature Communications, and holds 5 patents.
Authored >15 publications, including papers in top-tier journals such as Nature Communications, and holds 5 patents.
Education
- 2013-2019 PharmD, Moscow State University, Faculty of Medicine.
Experience
- 2018-2024: Medicinal chemist at Insilico Medicine.
Conducted CADD for various therapeutic targets. Participated in software development (Chemistry42, Generative Biologics). Led several computational projects from idea to in vitro testing (QFASG, AlphaFoldOptimizer). - Co-authored 16 scientific publications (h-index is 7, Google Scholar account).
Conducted CADD for various therapeutic targets. Participated in software development (Chemistry42, Generative Biologics). Led several computational projects from idea to in vitro testing (QFASG, AlphaFoldOptimizer).
Education
- 2013-2019 PharmD, Moscow State University, Faculty of Medicine.
Experience
- 2018-2024: Medicinal chemist at Insilico Medicine.
Conducted CADD for various therapeutic targets. Participated in software development (Chemistry42, Generative Biologics). Led several computational projects from idea to in vitro testing (QFASG, AlphaFoldOptimizer). - Co-authored 16 scientific publications (h-index is 7, Google Scholar account).
Conducted CADD for various therapeutic targets. Participated in software development (Chemistry42, Generative Biologics). Led several computational projects from idea to in vitro testing (QFASG, AlphaFoldOptimizer).
Advisory Board
Education
- • 1982-1986 Ph.D., Biochemistry and Pharmacology, Moscow State University, Moscow, USSR. Advisor: Prof Lev S. Yaguzhinski. Thesis: Quantitative Structure-Activity.
- • 1977-1982 M.S., Chemistry, Moscow State University, Moscow, USSR.
Experience
- • Lead academic and research roles in cheminformatics, QSAR modeling, and computational toxicology.
- • Director, Laboratory for Molecular Modeling
Supervise interdisciplinary research in AI-based drug design, model validation, and chemical safety. - • Co-founder, Predictive, LLC
Developed AI tools to minimize animal testing in toxicology and risk assessment. - • Adjunct Professor, UNC Chapel Hill
Departments: Biomedical Engineering, Computer Science, Applied Physical Sciences. - • Scientific Contributions
Authored 300+ peer-reviewed publications. Key contributor to best practices in QSAR validation (h-index of 92, Google Scholar account).
Supervise interdisciplinary research in AI-based drug design, model validation, and chemical safety.
Developed AI tools to minimize animal testing in toxicology and risk assessment.
Departments: Biomedical Engineering, Computer Science, Applied Physical Sciences.
Authored 300+ peer-reviewed publications. Key contributor to best practices in QSAR validation (h-index of 92, Google Scholar account).
Dr. Alexander Tropsha
K.H. Lee Distinguished Professor and Associate Dean for Pharmacoinformatics and Data Science at UNC Eshelman School of Pharmacy
Education
- • 1982-1986 Ph.D., Biochemistry and Pharmacology, Moscow State University, Moscow, USSR. Advisor: Prof Lev S. Yaguzhinski. Thesis: Quantitative Structure-Activity.
- • 1977-1982 M.S., Chemistry, Moscow State University, Moscow, USSR.
Experience
- • Lead academic and research roles in cheminformatics, QSAR modeling, and computational toxicology.
- • Director, Laboratory for Molecular Modeling
Supervise interdisciplinary research in AI-based drug design, model validation, and chemical safety. - • Co-founder, Predictive, LLC
Developed AI tools to minimize animal testing in toxicology and risk assessment. - • Adjunct Professor, UNC Chapel Hill
Departments: Biomedical Engineering, Computer Science, Applied Physical Sciences. - • Scientific Contributions
Authored 300+ peer-reviewed publications. Key contributor to best practices in QSAR validation (h-index of 92, Google Scholar account).
Supervise interdisciplinary research in AI-based drug design, model validation, and chemical safety.
Developed AI tools to minimize animal testing in toxicology and risk assessment.
Departments: Biomedical Engineering, Computer Science, Applied Physical Sciences.
Authored 300+ peer-reviewed publications. Key contributor to best practices in QSAR validation (h-index of 92, Google Scholar account).