Delivering for ALS patients: ‘Good Decision Tools’ in Research are good for patients and good economics
Amyotrophic lateral sclerosis (ALS) is a fatal late-onset neurodegenerative disorder which affects motor neurons in the brain and spinal cord. Degeneration of motor neurons results in muscle weakness, atrophy, and eventually paralysis. Symptoms initially affect the upper extremities, but as the disease progresses muscles responsible for breathing, swallowing, and speaking are affected, leading to respiratory failure.
Progression of symptoms follows a linear decline, and survival from time of diagnosis is on average just 15.8 months. Compared to other neurodegenerative diseases (AD, PD, HD, MS), ALS has a rapid fatal progression. Whilst there are some genetic forms of the disease (C9ORF72, SOD1, TARDBP, and FUS) these make up just 5-10% of ALS patient. The majority of patients have sporadic ALS with no clear aetiology.
Treatments are limited, with approved drugs riluzole and edaravone having some benefit on survival and reduction in the rate of disease progression, respectively. In clinical studies, riluzole resulted in a 2–3-month survival benefit, although real-world data suggests the range is 6-19 months.
Recently (2023), the FDA approved Qalsody, an antisense oligonucleotide (ASO) drug. This drug is specifically for patients with a mutation in the SOD1 gene. Qalsody reduces the production of the SOD1 protein. The drug was approved under the accelerated approval pathway, a regulatory path which allows drugs to be approved based on ‘surrogate endpoints’ for severe diseases with limited treatment options. Qalsody approval was based on a reduction of neurofilament light chain (Nfl) a blood-based biomarker of neurodegeneration. The drug has since received approval under ‘exceptional circumstances’ by EMA (2024) and ‘conditional approval’ from Health Canada (2025).
Whilst the approval of Qalsody is encouraging its use is limited to ALS-SOD1 patients. Failure of new medicines in ALS clinical trials is more the norm. Recent failures include pegcetacoplan (a complement C3 inhibitor), reldesemtiy (a fast skeletal muscle troponin activator), and two eIF2B activators (fosigotifator and DNL343). Another drug, Relyvrio, which was also given accelerated approval by the FDA after positive Phase 2 trial results, was subsequently taken off the market after it failed in a pivotal Phase 3 trial.
How can success rates improve? R&D is a complex multifaceted endeavour, and multiple things need to happen to hasten the arrival of successful medicines.
Biomarkers: the approval of Qalsody based on reduction of Nfl is an encouraging step. Using biomarkers in blood to diagnose neurodegenerative diseases can accelerate R&D. However, the relationship between the biomarker and neurodegeneration in the brain needs to be well-founded. Studies have shown that in ALS, Nfl in blood & CSF are significantly higher compared to other neurodegenerative diseases (AD, PD, MS). Also, higher Nfl levels are associated with more rapid ALS disease progression and reduced survival time. Measuring and targeting Nfl levels in blood and CSF in preclinical research provides a bona fide translational tool (1,2).
There are, a myriad of Cellular Mechanisms proposed to be important in driving disease in ALS: mitochondrial dysfunction, oxidative stress, inflammation, excitotoxicity, TDP-43 mislocalisation, dysfunctional proteostasis, amongst others. Reliable and validated assay are important tools for interrogating these mechanisms and pivotal in decision making.
Picture reference: Nature Reviews Drug Discovery, 2022.
Utilising humanised tools, like iPSC derived motor neurons from healthy donors and ALS patients in research could improve the likelihood of success. This is because humanised cells provide the species relevant cellular and molecular (patho)physiological context for testing new therapeutics.
These are just some research ‘decision tools’ to consider in improving success rate in ALS. From a broader R&D economics perspective good ‘decision tools’ in research have a $ value since they increase the $ value of a therapeutic asset or research programme. This is because they can drive better downstream decisions. The availability of good ‘decision tools’ should drive R&D capital allocation to assets and research with increased probability of success in ALS (3).