Download the white paper
Oncology remains the dominant focus in biopharmaceutical R&D, accounting for nearly 40% of the global pipeline. Yet development costs regularly exceed $2 billion per approved therapy, and preclinical predictability remains a persistent challenge.
Part of that challenge comes down to data. Oncology models generate large volumes of complex information: genomics, pathology, pharmacology, and biochemistry, often scattered across disconnected systems. This slows down research and adds unnecessary manual work.
At ChemPartner, we’ve built the Biology Database to address this directly. It’s an integrated translational research resource combining a comprehensive tumor model portfolio with enzymology data, more than 100 million experimental data points, and analytical tools that support decision-making from target validation through IND-enabling studies.
To share how this works in practice, we’re highlighting our latest white paper, which explores:
– How the database evolved from a tumor model catalog into an integrated translational research resource
– Why combining tumor model and enzymology data supports faster model selection and lead optimization
– Practical applications across the drug discovery pipeline, from target validation through IND-enabling studies
If you’re working in oncology drug discovery, feel free to reach out to request the white paper.
Download the white paper
