The convergence of artificial intelligence (AI) with drug development represents a transformative shift in the pharmaceutical industry, with potential benefits extending across various stages of the development lifecycle. AI plays a crucial role in expediting the delivery of medications to market by streamlining and augmenting procedures throughout drug development. It facilitates the acceleration of genetic sequencing, the prediction of drug efficacy and side effects, and the management or generation of extensive volumes of documents and data vital for pharmaceutical products. 

Through machine-learning analysis, AI enables faster decision-making regarding drug development pathways by preemptively identifying potential failures, such as early detection of toxicities. This capability not only saves valuable time and resources but also enhances efficiency within the drug development process. Moreover, AI holds promise for numerous applications in clinical trials, both in the short and long term. These include seamlessly integrating phases I and II of clinical trials, devising innovative patient-centered endpoints, and gathering and analyzing Real World Data to glean actionable insights.

Promising trends and future outlook: 

Despite being in its nascent stages, AI-enabled drug development has garnered significant attention and investment, driven by its promising return on investment and potential to revolutionize the field. Recent estimates suggest that by 2025, AI could play a pivotal role in the discovery of up to 30% of new drugs, reflecting a market with a staggering $50 billion addressable value. Notably, a 2022 BCG report highlighted the substantial time and cost savings AI could offer, particularly in the preclinical stages of drug discovery, projecting efficiencies ranging from 25% to 50%. Reinforcing this momentum, the FDA has acknowledged the rising integration of AI and machine learning (ML) in drug development, emphasizing the need for an adaptable regulatory framework to foster innovation while ensuring public health standards are upheld. These developments underscore AI's burgeoning role in shaping the future landscape of pharmaceutical innovation.

Big Pharma Ramping up Investment:

There is a growing acknowledgment of the transformative impact of AI within the pharmaceutical sector. This acknowledgment is underscored by the shift in discussions from theoretical possibilities to tangible advancements. With compelling new use cases, pharmaceutical companies are increasingly investing in AI for drug discovery and development. It emphasizes AI's contributions not only to target discovery but also to substantial improvements in manufacturing processes and clinical trials.

• In December 2023, Sanofi entered a $140M deal with Aqemia, a French pharmaceutical technology company who have developed technology that incorporates physics-based algorithms and generative AI to expedite drug discovery processes. Sanofi will apply this technology to identify and create small molecules with potential across various therapeutic areas, while funding the further refinement of Aqemia’s methods to drive progress in drug discovery. Sanofi has also invested in other AI companies including a deal totalling $270M with Owkin in 2021, and another deal in 2022 with Exscientia.

• In 2023 Merck announced alliances with major AI companies BenevolentAI and Exscientia to enhance its drug discovery process, and generate novel small-molecule candidates, in oncology, neurology, and immunology, expanding its use of AI-driven design and discovery capabilities. 

• AstraZeneca launched Evinova, focusing on providing digital health solutions, including AI-driven solutions, to optimize clinical trial design and delivery, and reduce development costs. 

• In January 2024, Novo Nordisk announced its plans to open a new, AI-based research facility to advance drug discovery operations in London. This follows its recent partnership with Valo Health to discover and develop novel treatments for cardiometabolic disease using AI. 

AI has the potential to significantly reshape the competitive landscape of the pharmaceutical industry. With big bets, the industry's approach to disease treatment is undergoing rapid transformation as a result. As the competitive stakes heighten, organizations are compelled to not only invest but to swiftly build capabilities, to get ahead of competitors and secure their position at the forefront of this transformative wave. 

While AI holds promise for drug discovery, its full impact remains to be seen. Success in biopharma AI hinges on data generation and curation, with challenges related to data complexity and its applicability to desired outcomes. Big Tech companies, known for their proficiency in handling extensive digital data, continue to invest billions into AI technologies to make inroads into AI based drug discovery. 

NVIDIA has been actively engaging in high-profile collaborations in healthcare, particularly focusing on generative AI capabilities. These collaborations span various sectors including imaging, medtech, drug discovery, and digital health. At the 2024 GTC AI conference, NVIDIA announced partnerships with four companies to develop drug discovery platforms, utilizing NVIDIA’s BioNeMo platform and quantum cloud services. This move aligns with the company's strategy to capitalize on the burgeoning healthcare AI market, evidenced by its stock price surge and investments in AI solutions for healthcare. 

NVIDIA's collaborations with companies like Cadence Design Systems, Cognizant, QC Ware, Microsoft, Johnson & Johnson MedTech, and GE HealthCare highlight the growing importance of AI technologies like genAI and BioNeMo, in accelerating drug discovery processes, enhancing surgical procedures, and improving medical imaging efficiency. AstraZeneca and several startups, including Insilico Medicine and Evozyne, are also BioNeMo customers. 

Eli Lilly and Novartis have both forged partnerships with Isomorphic Labs, an Alphabet subsidiary. The agreement with Lilly, a multi-year strategic research alliance aimed at discovering small molecule therapeutics for various targets, offers the possibility of receiving up to $1.7 billion in milestone payments along with royalties. Likewise, the collaboration with Novartis is noteworthy, centering on the discovery of small molecule therapeutics for three undisclosed targets, potentially fetching up to $1.2 billion in milestone payments, alongside royalties.

A growing investment from pharma, and recent landmark deals with Big Tech demonstrate a significant shift in the industry towards integrating AI into the drug discovery process. With rapidly advancing AI capabilities, continued collaboration between big tech and pharma companies holds great potential for the future of drug discovery.

What’s next for AI in drug discovery 

There is no doubt that AI has the potential to create molecules and therapies that were never possible before. Experts are excited about the possibility that AI can not just predict but also invent new biology and pathways. Both pharmaceutical and big tech companies have embarked on ventures into utilizing AI for drug discovery and development, but unlocking its full potential requires both deep understanding and patience. It is imperative that pharma understands that significant productivity gains may not be immediate. Despite challenges such as complex biological systems and regulatory hurdles, AI offers the pharmaceutical industry a unique opportunity to innovate in science and patient care. Recognizing this potential, companies must continue to invest in understanding, implementing, and scaling AI applications in drug discovery and development.