The Hemophilia Target Landscape

No cure exists for hemophilia, necessitating frequent, tailored interventions. The imperative for improved treatments hinges on identifying relevant biological targets. Utilizing Causaly, we explored potential targets for hemophilia investigated in animal models.

Hemophilia is a rare X chromosome-linked bleeding disorder affecting 1 in 5,000 male births worldwide.¹ Caused by mutations in factor VIII (FVIII) and IX (FVIX) genes encoding for critical blood clotting proteins,² hemophilia leads to spontaneous, prolonged bleeding in addition to joint pain.

There is no cure for hemophilia. While current treatments like clotting factor supplements help to manage bleeding, they require necessitate frequent body-mass–dependent injections on-demand.³ This highlights the urgent need for more effective treatments to improve patient quality of life.

Most often, the development of new medicines begins with biological targets implicated in a disease.⁴ Identifying relevant targets that are specific to a disease is crucial to accelerating development of effective drugs with minimal side effects. Here, we used Causaly to identify relevant targets for hemophilia.

Causaly can expedite the target discovery process by rapidly identifying potential targets implicated in a disease. This allows scientists to prioritize more promising targets from the exponentially growing biomedical literature by separating the signal from the noise.

Almost 200 targets for hemophilia were uncovered by Causaly, as shown in Figure 1. Approximately 60 targets have been reported in the literature since 2018. Around 25 targets have been associated with animal studies.

Causaly’s AI reads like a human, understanding both context and nuance. As such, the directionality of target-disease relationships can be deduced. This includes upregulation, downregulation, unidirectional and bidirectional relationships, along with their refuting counterparts. As examples, we have selected targets with downregulated or unidirectional relationships in hemophilia.

The hemophilia treatment landscape demands innovative and effective therapies. An extensive understanding of disease biology and therapeutic targets is a crucial step in this process. Causaly can streamline target identification, enabling drug discovery scientists to prioritize promising targets to drive more effective target selection.