|||
The number seems daunting: fewer than 500 druggable targets exist.
Scientists are driven to understand the biological causes of diseases by identifying genes, proteins, and processes linked to them. While this expands our knowledge of how diseases work, society expects these discoveries to lead to real treatments and cures that alleviate suffering—what is often referred to as the ‘Aspiration-Expectation Gap’.1
There are two established strategies to address this limitation:
Polypharmacology
Shifting from the traditional ‘one compound — one target’ approach to targeting multiple molecular pathways simultaneously. This method is proving effective in cancer treatment and is actively studied in Quantitative Systems Pharmacology (QSP).
Small-Molecule Probes
Probes are not drugs but powerful research tools that can interact with hard-to-target molecules, providing insights into their functions. These insights could eventually lead to new therapeutic strategies for diseases once thought untreatable.
What will truly shape our digital transformation journey in Digital Therapeutics (DTx) is bridging this Aspiration-Expectation Gap through innovative drug-device combination treatments. These solutions will be model-informed, QSP-like, integrating AI tools such as data assimilation and Kalman filters to enhance predictive accuracy.
Altmann et al., 2009, ChemBioChem.↩︎