Cash flow & capital structure
Examining financial records, debt obligations, and future funding needs.
02 / Research
Financial risk and computational gastric cancer research, supported by shared data and modeling expertise.
AI Finance
The finance department studies company finances, capital structure, cash flow, and liquidity. Its work considers how obligations and funding needs relate to the cash a company can generate.
Statistical analysis and machine learning help organize information, compare scenarios, and identify assumptions that need closer attention. Research remains tied to its market context and the limits of the underlying data.
Examining financial records, debt obligations, and future funding needs.
Comparing how conclusions change when conditions or assumptions become less favorable.
AI Medicine
The medical department uses computational methods to study gastric cancer and support early-stage targeted anticancer drug research.
Its work brings together molecular evidence, drug-response findings, and questions for further investigation. Three connected areas are evaluated separately.
Medical research priorities
Comparing evidence on biomarkers, drug sensitivity, and resistance across studies, with attention to differences in samples, methods, and findings.
Examining the evidence linking possible targets, tumor biology, and drug mechanisms, and identifying the questions that remain open.
Exploring whether computational methods can narrow the range of candidates for further study and offer more focused leads for experimental research.
From analysis to evidence
Computational associations, rankings, and predictions help frame the next research question. Experimental work, safety evaluation, and clinical research are needed to determine whether a candidate can become a treatment.
Specialists in the relevant scientific disciplines assess biological and medical questions. Katharina’s role is to support the people, priorities, and resources that make that work possible.