3 citations · 5 across the 5 of their papers we have counts for
5 papers
MADD: Multi-Agent Drug Discovery Orchestra
Gleb V. Solovev, Alina B. Zhidkovskaya, Anastasia Orlova +18
Hit identification is a central challenge in early drug discovery, traditionally requiring substantial experimental resources. Recent advances in artificial intelligence, particula…
Pharmacophore-Guided Generative Design of Novel Drug-Like Molecules
Ekaterina Podplutova, Anastasia Vepreva, Olga A. Konovalova +3
The integration of artificial intelligence (AI) in early-stage drug discovery offers unprecedented opportunities for exploring chemical space and accelerating hit-to-lead optimizat…
Benchmarking Agentic Systems in Automated Scientific Information Extraction with ChemX
Anastasia Vepreva, Julia Razlivina, Maria Eremeeva +10
The emergence of agent-based systems represents a significant advancement in artificial intelligence, with growing applications in automated data extraction. However, chemical info…
Hybrid Generative AI for De Novo Design of Co-Crystals with Enhanced Tabletability
Nina Gubina, Andrei Dmitrenko, Gleb Solovev +7
Co-crystallization is an accessible way to control physicochemical characteristics of organic crystals, which finds many biomedical applications. In this work, we present Generativ…
Unveiling the Potential of AI for Nanomaterial Morphology Prediction
Ivan Dubrovsky, Andrei Dmitrenko, Aleksei Dmitrenko +2
Creation of nanomaterials with specific morphology remains a complex experimental process, even though there is a growing demand for these materials in various industry sectors. Th…