A Scalable Screening Platform to Accelerate Early Drug Discovery for Diverse ALS Subtypes
Abstract
How can we accelerate drug discovery for ALS patients? A major challenge in the development of effective therapies is variability from one ALS patient to another, including disease onset, progression, and genetics. A key lesson from cancer is that identifying disease subtypes can dramatically accelerate the development and approval of effective therapies. Treatments that are effective for one subset of patients can have little or no benefit to others; for example, different drugs are used for breast cancer patients that are HER2 positive versus triple negative. Could a targeted treatment strategy benefit ALS patients? And, if so, how do we identify ALS disease subtypes, particularly given that the cause of ALS is unidentified for the vast majority of patients? How can we find ALS subtypes? In order to identify subtypes, we must look across a large and diverse population of ALS patients. We will work with patient-derived fibroblasts (obtained from a skin punch), which capture genetic and age-related risk factors for ALS. Importantly, patient fibroblasts can be grown in large and reproducible batches, making our platform highly scalable and cost effective (<$1 per condition). To identify subpopulations of patient samples, we will use a robotic microscopy system and machine learning algorithms to measure how ALS and healthy cells look and respond to stress. Our system will measure many different properties and pathways of cells to identify those that change in different subtypes. ALS subtype signatures we identify from the easy-to-assay fibroblasts will be validated in ALS patient-derived motor neurons. Our strategy allows us to assign patients to ALS subtypes based on these cellular signatures, regardless of whether there is a known genetic cause. How will identifying ALS subtypes translate into therapies? In principle, we would have to screen thousands of potential drug targets across hundreds of patients to identify bespoke therapeutic strategies--an intractable task. The benefit of using our platform is that we can identify a small number of patient cell lines to represent each ALS subtype. Using a smaller number of representative cell lines will allow us to search over 7,000 proteins that have been determined to be druggable. The results of these efforts will be short lists of drug targets that push cells in different ALS subtypes towards health. It is our hope that, by focusing on druggable targets, we will dramatically shorten the time between target discovery and translation to therapeutics. With an aggressive timeline, it is possible that compound leads that modulate these targets in cells can be developed within two years and then optimized for clinical trials. By directly incorporating patient diversity into the early stages of drug discovery, we will accelerate development of bespoke therapeutics for ALS patients.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 05, 2021
- Source ID
- W81XWH2110094
Entities
People
- Steven Altschuler
Organizations
- United States Army
- University of California, San Francisco