Irina Bilous

Artificial Intelligence (AI) is steadily making its presence felt across various sectors, including the pharmaceutical industry. Among the multiple applications of AI in this field, immunotherapy - a treatment method that utilizes the body's immune system to combat diseases, notably cancer - is seeing a significant influence. The integration of AI can potentially enhance treatments and patient care by making it more precise and personalized.

Historically, the approval rate for medicines treating central nervous system (CNS) disorders was low. By 2022, the success rate for CNS assets from phase 1 through to regulatory submission was only 5–6%.

The failure of pharmaceutical companies to bring CNS medications to the market can be attributed to factors such as a limited understanding of disease mechanisms and challenges in delivering drugs across the blood-brain barrier. Nevertheless, recent technological advancements and an improved understanding of disease pathophysiology led to expanding the CNS pipeline.

A recent report shows that the CNS pipeline has grown by 31%, constituting 14% of the overall industry R&D pipeline. Moreover, the approval of the first drug for spinal muscular atrophy (SMA) developed by Ionis Pharma and Biogen was a significant stride that revitalized interest in the field and demonstrated the ability of innovative treatments to address complex neurological disorders.

The clinical trial is a critical stage of drug development workflow, with an estimated average success rate of about 11% for drug candidates moving from Phase 1 towards approval. Even if the drug candidate is safe and efficacious, clinical trials might fail due to the lack of financing, insufficient enrollment, or poor study design.

Artificial Intelligence (AI) is increasingly perceived as a source of opportunities to improve the operational efficiency of clinical trials and minimize clinical development costs.  Typically AI vendors offer their services and expertise in the three main areas. AI start-ups in the first area help to unlock information from disparate data sources, such as scientific papers, medical records, disease registries, and even medical claims by applying Natural Language Processing (NLP). This can support patient recruitment and stratification, site selection, and improve clinical study design and understanding of disease mechanisms. As an example, about 18 % of clinical studies fail due to insufficient recruitment, as a 2015 study reported.

The fusion of artificial intelligence (AI) with multi-omics - a comprehensive study encompassing genomics, transcriptomics, proteomics, metabolomics, and other related fields - is heralding an era of speedier, more efficient drug discovery. AI has been disrupting various sectors, but its potential in revolutionizing the drug discovery process - traditionally a complex, time-consuming, and expensive undertaking - is garnering significant attention. The integration of AI with multi-omics approaches is enhancing the predictive power of drug discovery algorithms, minimizing risks, and expediting the journey from the bench to the bedside.

Verge Genomics, a frontrunner in the implementation of AI in drug discovery, recently concluded the Phase 1 clinical trial of VRG50635, an investigational drug for Amyotrophic Lateral Sclerosis (ALS). The drug, developed through artificial intelligence-driven methods, was well tolerated and demonstrated safety in healthy adult volunteers. The clinical results position VRG50635 as a potential best-in-class therapeutic for all forms of ALS.

IgGenix, Inc., a California-based preclinical antibody discovery and development company, recently reported advances towards a potential therapeutic solution for peanut allergies based on IgG4 monoclonal antibodies.

Certara, a leader in biosimulation, has recently expanded the horizons of AI in drug discovery with the introduction of artificial intelligence (AI) capabilities and data fabric connectivity to its clinical trials outcome analytics platform, CODEX.

Seqera Labs, recognized for its secure workflow orchestration software in the life sciences domain, is aligning forces with Genomics England, a government-owned entity, which initiated the notable 100,000 Genomes Project in alliance with the NHS. This collaboration aims to enhance the scope and proficiency of whole genome analysis, paving the way for a broader patient base to avail genomic healthcare benefits.

Valo Therapeutics Oy (ValoTx), a frontrunner in the development of advanced immunotherapies for cancer, has initiated its Phase I trial of PeptiCRAd-1, a pioneer in the realm of immuno-oncology. The first participant, enrolled in this Germany-based trial, has received the treatment without any immediate safety issues, according to the company's recent press release.

PharmEnable, an innovative drug discovery firm, recently secured $7.5M in Pre-Series A financing, reflecting growing confidence in its proprietary AI-based drug discovery platform and potential contributions to the treatment of cancer and neurological diseases. This move signifies the latest milestone in the integration of AI technology into drug discovery, a trend that's been steadily reshaping the biopharma landscape.