Target Identification in Prostate Cancer

Limited therapeutic efficacy and drug resistance in advanced-stage prostate cancer contributes to poor patient outcomes,¹ highlighting the need for targeted therapies with alternative mechanisms of action. Here, we leveraged human-centric AI to accelerate target identification for prostrate adenocarcinoma.

Identifying therapeutic targets is crucial for developing more effective treatments. In fact, 40% of efficacy-related projects failures are attributable to poor target-disease understanding.² Causaly can streamline target discovery by accelerating the identification of promising targets. Here, we used Causaly to uncover targets for prostate adenocarcinoma – the most common type of prostate cancer.

Using Causaly, 750+ targets for prostate adenocarcinoma were identified in seconds as shown in the dendrogram in Figure 1. More than 75% of these targets were reported in the literature in the last 5 years, with ~400 targets reported in primary data.

Causaly understands context and nuance and can extract directional target-disease relationships, including upregulation, downregulation, unidirectional and bidirectional relationships. Figure 2 shows examples of targets for prostate adenocarcinoma by relationship type.

With Causaly, targets can be prioritization by the amount of evidence, novelty and the strength of the evidence for role of the target in disease pathophysiology:

Current challenges in metastatic prostate adenocarcinoma include poor therapeutic efficacy and chemotherapeutic resistance. Thus, there is a crucial need for developing alternative and targeted therapies. With Causaly, drug discovery scientists can focus their discovery programs by accelerating target identification and prioritizing validated targets and exploring more novel avenues.