Perturbation modeling aims to find a model that can accurately predict the outcome of a perturbation on a given cell, such as a drug or CRISPRi intervention. Creating a massive amount of perturbation data is a challenging endeavor due to technical and financial constraints, which inhibit the progress of creating a biologically… read more
The ADC field is advancing rapidly, with 17 ADCs approved to date, including 13 by the U.S. FDA, and more than 300 candidates in clinical development. Among these, dual-payload conjugates and other next-generation designs are emerging to address limitations of current ADCs. read more
Modeling cellular phenotypes is a fundamental challenge in computational systems biology. Accurately predicting cell fate can advance our understanding of both healthy and diseased states and facilitate the identification of novel therapeutic targets. Post-perturbation transcriptomics data are particularly suited for training computational models because the causal relationship between known perturbations and the… read more
ADCs represent a new era of targeted cancer therapy with 15 approved drugs. However, over 100 discontinued ADC programs and a similar number of active clinical trials highlight the difficulties of identifying the optimal combination of antibody, target, payload, linker, drug-antibody ratio and indication. Understanding mechanisms and factors contributing to different levels… read more
RAC1 and CDC42 are members of the Rho family of small GTPases that promote cell survival, cell cycle progression, proliferation, migration and invasion, therefore play a key role in anchoring independent growth, cell transformation and metastasis. Targeting RAC proteins and CDC42 holds great anti-tumoral potential. We used the Simulated Cell to perform… read more
