2024 Healthcare, Consumer & Wellness Magazine

22 Healthcare, Consumer &Wellness • 23 Lack of diversity also remains a persistent issue. Instances include the phase 2 clinical trial for crenezumab, a monoclonal antibody under investigation as an Alzheimer’s treatment. FDA analysis found that over 97% of trial participants were white and just 2.8% were Hispanic despite the fact that Hispanic people are 1.2 times more likely to develop the disease. AI can help by enabling CROs to decentralize clinical trials using remote data collection and monitoring. In February 2024, for example, CRO ICON announced a preliminary agreement to use Intel’s edge-to- cloud AI solution, Pharma Analytics Platform, to achieve this. This eliminates the need for patients to travel to sites. Sensors and wearables will capture data and monitor trial adherence from participants who will also have access to a dedicated app to submit findings and images. Integration with ICON’s Direct-to- Patient Call Center (DPC) provides continuous compliance monitoring. The platform also applies machine learning techniques to measure symptoms and quantify medication efficacy and dose responses. The move to more diverse and decentralized clinical trials also has implications for the supply chains that support them. “They’re getting longer and more complex,” Buonvino comments. “This entails new logistical challenges such as ensuring that lab test kits don’t expire, or samples don’t get delayed or lost in transit.” He adds that “payment systems are changing too as cross-border needs become greater.” For the pharma and biotech industry, speeding up the delivery of safer and more effective drugs to a wider global market is AI’s end goal. In one 2023 report, research funder Wellcome and consulting firm BCG concluded that AI could yield time and cost savings of at least 25% to 50% in drug discovery at the preclinical stage. One such player is Shanghai-based Zai Lab. The company targets diseases with unmet needs such as pancreatic cancer, which, has one of the poorest five-year cancer survival rates worldwide, at around 5%. Zai Lab has a partnership with fellow Chinese biotech AlphaMa to screen for novel molecular targets using the latter’s AI platform. Based in Suzhou, the company helps to screen candidates with high clinical potential more efficiently. Other companies such as US-based Generate:Biomedicines are using generative AI to program novel proteins not previously found in nature with targeted biological and therapeutic properties. One of the most well-known in the field is Google DeepMind. In October 2023, the UK-based company unveiled a new version of its AI model, AlphaFold. This not only provides more accurate data about nearly all the catalogued proteins known to science but can also now unlock the structures of ligands (molecules that bind to proteins and play a key role in cell signaling), plus nucleic acids (RNA and DNA). Optimizing quality control and process efficiency AI’s second key application concerns clinical trials. Here, it can help clinical research organizations (CROs) to identify and recruit participants far more quickly and effectively so that trials proceed on time and have the right gender and ethnic mix. There is significant room for improvement. Currently, more than 80% of clinical trials globally fail to hit their recruitment targets on time. from start to finish. Buoyed by that success, the pharma industry’s focus has now shifted to AI and especially how generative AI can help to create drugs from those septillion plus drug- like molecules (1 followed by 24 zeros) more quickly and effectively. Better prediction modeling and drug design “We’re in the early stages of a golden age for drug development,” says Steven Buonvino, UK, Europe, Middle East and North Africa Sales Head of Healthcare, Consumer & Wellness for Citi Treasury and Trade Solutions (TTS). “The number of pharma companies with active pipelines is double what it was a decade ago. AI is starting to act as an accelerant across the entire industry chain.” Stars align for drug development Applying AI to drug discovery and clinical trials is spurring an expanding universe of innovative treatment options for existing and previously incurable diseases. There are more drug-like molecules in the observable universe than there are stars. Yet, while the positive implications for human health are enormous, the process of screening and turning any of them into life-saving drugs is both lengthy and costly. New drugs typically take 10 to 15 years to gain regulatory approval, at an average cost of $2.6 billion. And these are just the ones that make it through to end-consumers. Only 12% of new molecular entities that enter clinical trials eventually receive Food and Drug Administration (FDA) approval, according to Pharmaceutical Research and Manufacturers of America (PhRMA). The failure rate including pre-clinical trials is even higher. There has been one notable exception in recent years: the Covid-19 vaccine, which took less than one year The number of pharma companies with active pipelines is double what it was a decade ago. AI is starting to act as an accelerant across the entire industry chain” 80% Global clinical trials Don’t hit recruitment targets on time At Citi, we are supporting our clients’ broadening digitalization, financing and supply chain management needs at a time of unprecedented change in the scope, structure and speed required to successfully bring newdrugs tomarket.