Target-Based Drug Discovery Begins with Understanding Disease Pathophysiology

Target-based drug discovery begins with understanding the physiological basis of the disease, and the subsequent abnormal or deviant pathways and targets responsible for the disease phenotype. A foundational understanding of disease pathophysiology therefore serves as a roadmap for drug development success.

Diseases are multifaceted, often exhibiting heterogeneity and diverse manifestations, with complex interplays between genetic, environmental and lifestyle factors. The abundance of scientific data further complicates the picture. Traditional keyword searching can return thousands of papers for a given disease, presenting limited opportunity for knowledge discovery and hypothesis generation. Moreover, these results are not always comprehensive, highlighting the need for improved search strategies.

By leveraging AI, researchers can comprehend the entire volume of biomedical literature in seconds, extracting relevant evidence from millions of documents. Our multi-hop module can uncover hidden relationships in biomedical data, allowing you to connect seemingly unrelated concepts to form the basis of a hypothesis. As an example, we have used Causaly Cloud to understand genes, proteins and potential mediators implicated in Graves’ disease, using the multi-hop module to generate new hypotheses.

With Causaly, 500+ genes and proteins affecting Graves’ disease were uncovered, around 20% of which have been reported in preclinical studies. Using the advanced filtering, results were refined down to 62 genes and proteins reported in the last 5 years. Delving deeper revealed around two thirds were reported in primary data.

Further prioritization by evidence strength enabled the identification and subsequent exploration of pentraxin 3 (PTX3). By utilizing the mult-hop module, more than 30 genes were shown to indirectly link PTX3 with Graves’ disease. Here, Toll-like receptor 4 (TLR4) was selected as an example.

Data from a recent study revealed that the PTX3/TLR4 autocrine loop sustains the growth and aggressiveness of triple-negative breast cancer cells and determines the antitumor response to TLR4 inhibition.² Another study found that silencing of PTX3 alleviated LPS-induced inflammatory pain via the regulation the TLR4/NF-κB signaling pathway in mice.³

TLR4 has also been implicated in Graves’ disease. Results from a clinical study showed higher expression of TLR4 on monocytes among newly diagnosed Graves’ disease patients compared to normal individuals.⁴ In the same study, TLR4 expression significantly decreased among patients after carbimazole.⁴

Given the role of PTX3 in the activation and regulation of TLR4, along with the observed elevated expression of TLR4 in Graves’ disease patients, it can be hypothesized that PTX3 may mediate Grave’s disease via the TLR4 pathway.

Unraveling disease pathophysiology paves the way for targeted therapies that address the root cause of the disease. With Causaly, seemingly unrelated concepts can be uncovered from the wealth of biomedical data, empowering scientists to generate transformative hypotheses for their research.