About Genentech

Adrian Chan has established himself as a key contributor to Genentech's data science initiatives, particularly in clinical reporting and R programming. As an instructor for "Hands On Clinical Reporting Using R," he helps develop and deliver practical training in clinical data analysis and reporting methodologies. His work at Genentech, a pioneering biotechnology company with over 40 years of industry leadership, focuses on making complex clinical data analysis accessible and actionable. His expertise in R programming and clinical reporting contributes to Genentech's mission of advancing healthcare through data-driven insights. Through his teaching role, he helps bridge the gap between theoretical data science concepts and practical applications in clinical research and reporting.

Dinakar Kulkarni has established himself as a leader in developer tooling and clinical data science at Genentech. As Developer Tooling Lead, he specializes in implementing data science principles in clinical reporting environments. His expertise is demonstrated through his role as instructor for the course "Making Data Science Work for Clinical Reporting," where he teaches intermediate-level concepts combining data science tools with clinical reporting practices. His course covers crucial areas including version control, risk assessment in codebases, and the implementation of data science principles in clinical settings. His work focuses on bridging the gap between traditional clinical reporting and modern data science methodologies, helping professionals understand how to effectively apply tools like R and Python in clinical contexts. His expertise in DevOps practices and agile methodologies contributes to Genentech's mission of advancing healthcare through innovative data science applications.

Holger Langkabel has established themselves as a Senior Data Scientist at Genentech/Roche, bringing a unique combination of statistical expertise and business analysis skills to pharmaceutical research. Their academic background includes an MSc in Statistics from Berlin universities and a BSc in International Economics and European Studies from Tübingen University. Since joining Roche in 2016, they have evolved from a statistical programmer to a business analyst role focusing on Roche's statistical computing environment. Their expertise lies in designing high-quality, fit-for-purpose system landscapes that balance user needs with practical and regulatory requirements in the pharmaceutical industry. Their dual background in statistics and economics enables them to bridge the gap between technical statistical computing and business requirements, particularly in regulated environments. As an instructor, they share their expertise through courses on clinical reporting, helping others navigate the complex intersection of data science and pharmaceutical research.

Jana Stoilova has established herself as a Data Scientist at Genentech, specializing in clinical data analysis and reporting. As an instructor for the "Hands On Clinical Reporting Using R" course, she shares her expertise in using open-source R packages for clinical data reporting tasks. Her teaching focuses on the clinical data flow process, from raw data through SDTM and ADaM to final outputs. Her work contributes to the industry's transition toward open-source tools in pharmaceutical research, helping professionals understand and implement modern data science approaches in clinical reporting. At Genentech, she applies her expertise to bridge the gap between traditional clinical reporting methods and contemporary data science practices.

Joel Laxamana has established himself as a data science professional at Genentech, specializing in clinical reporting and R programming. As an instructor for the "Hands On Clinical Reporting Using R" course, he helps professionals develop practical skills in using open-source R packages for clinical data reporting tasks. His teaching focuses on the clinical data flow process, from raw data through SDTM and ADaM to final outputs. His expertise includes working with CDISC standards and implementing data science principles in clinical settings. At Genentech, he contributes to the industry's transition toward open-source tools in pharmaceutical research, helping bridge the gap between traditional clinical reporting methods and modern data science approaches.

Leena Khatri has established herself as a Data Scientist at Roche/Genentech and serves as Product Owner of NEST (Tables, Listings, TLG-Catalog). As an instructor for "Hands On Clinical Reporting Using R," she specializes in teaching professionals how to use open-source R packages for clinical data reporting tasks. Her expertise includes managing and developing tools for creating standardized clinical trial reports and analyses. As Product Owner of NEST, she leads initiatives to streamline the creation of tables, listings, and graphs for clinical reporting. Her work contributes to the industry's transition toward open-source tools in pharmaceutical research, helping bridge the gap between traditional clinical reporting methods and modern data science approaches.

Monica Daigl has established herself as a leading expert in Health Economics and Health Technology Assessment (HTA) at Genentech. As the instructor for "Data Science in Health Technology Assessment," she specializes in teaching key concepts and methods in health economics to professionals with backgrounds in data science and clinical studies. Her course covers crucial areas including economic evaluation principles, health-related quality of life measurement, and decision modeling techniques. Her expertise spans technical aspects such as cost-effectiveness analysis, quality-adjusted life years (QALYs), and economic modeling. Her teaching has received strong recognition, with a 4.5/5 rating from students. Through her work, she helps professionals understand the principles used by payers for reimbursement decisions, bridging the gap between data science, clinical research, and healthcare economics

Stefan Thoma has established himself as an Analytical Data Scientist at Roche/Genentech in Basel since 2021. His academic background includes a Master of Science in Methods, Cognition, and Perception from the University of Bern and a Master of Science in Statistics from ETH Zurich. His work focuses on developing open-source tools for pharmaceutical research, particularly through his involvement in the admiral R package, which is a key component of the Pharmaverse initiative. As a member of the Pharmaverse blog management team, he contributes to knowledge sharing within the pharmaceutical data science community. His expertise combines statistical methodology with practical applications in pharmaceutical research and development, helping advance data-driven approaches in drug development and clinical research.

Susanne Clinch has established herself as an expert in patient-centered outcomes research at Genentech. As the instructor for "Data Sciences in Pharma - Patient Centered Outcomes Research," she specializes in teaching how patient experience data and clinical outcome assessments (COA) can be used as evidence across drug development. Her course covers crucial areas including patient experience data collection, clinical outcome assessment development, and data analysis to evidence how patients feel, function, or survive in clinical trials. The curriculum she developed includes comprehensive coverage of COA background, patient experience data, qualitative research methods, psychometrics, and data interpretation. Her expertise helps professionals understand how to develop patient-centric measurement strategies and interpret clinical outcome assessment data effectively in pharmaceutical research.

Tatiana Alonso Amor has established herself as a data science professional at Genentech, specializing in clinical reporting and R programming. As an instructor for the "Hands On Clinical Reporting Using R" course, she helps professionals develop practical skills in using open-source R packages for clinical data reporting tasks. Her teaching focuses on helping learners understand the clinical data flow process, from raw data through SDTM and ADaM to final outputs. Her expertise includes working with CDISC standards and implementing data science principles in clinical settings. At Genentech, she contributes to the industry's transition toward open-source tools in pharmaceutical research, helping bridge the gap between traditional clinical reporting methods and modern data science approaches.

Vincent Shen has established himself as a data science professional at Genentech, specializing in clinical reporting and R programming. As an instructor for the "Hands On Clinical Reporting Using R" course, he helps professionals develop practical skills in using open-source R packages for clinical data reporting tasks. His teaching focuses on helping learners understand the clinical data flow process, from raw data through SDTM and ADaM to final outputs. His expertise includes implementing CDISC standards and modern data science principles in clinical settings. At Genentech, he contributes to the industry's transition toward open-source tools in pharmaceutical research, helping bridge the gap between traditional clinical reporting methods and contemporary data science approaches.