Bioinformatics and In Silico Analysis Laboratory (BISAL)

Cooperation Offer

 LBA, due to its expertise in modeling, especially with the use of artificial intelligence (AI) and machine learning (ML) techniques, deals with broadly understood predictive and exploratory modeling in the following areas:

•  Pharmacokinetics and pharmacodynamics,
•  Epidemiology,
•  Pharmacoeconomics,
•  Bioinformatics,
•  Quantitative Structure-Activity Relationships (QSAR) and Structure-Property Relationships (QSPR),
•  Correlation (IVIVC) and in vitro in vivo Extrapolation (IVIVE),
•  Image Analysis,
•  Cheminformatics.

Models are prepared based on the client’s data or based on data searched by the Laboratory team.

Equipment

• Two Fujitsu-Siemens PRIMERGY RX2540 M5 workstations each equipped with 2 Intel Xeon Gold 6230 CPUs; 1.5 TB RAM; Nvidia Quadro RTX 6000 graphics card
• Two Fujitsu Siemens PC management stations with 32-inch monitors

The system operates in a Linux environment, fully virtualized (VMware) and in model-agnostic mode, i.e. various processes are run and, depending on the needs, the necessary components are installed on dedicated virtual machines. Currently, R and Python environments and software from cheminformatics are available (Orca, Psi4, GROMACS). The SSH protocol ensures secure communication between virtual machines and the world.

About the team

Laboratory manager: Jakub Szlęk, PhD

A pharmacist with over 15 years of experience in applying artificial intelligence and machine learning in pharmaceutical sciences, an expert in data science and programming (Python, R, Java, Bash), with extensive experience in backend and frontend development. Author or co-author of more than 40 scientific publications and numerous conference presentations.

Technician: Natalia Łapińska, PhD Pharm

Pharmacist by education. Post-doc PhD at the Department of Drug Formulation Technology and Biopharmacy, Jagiellonian University Medical College. Specialist in QSAR and QSPR modeling, Python programmer.