Artificial intelligence (AI) is impacting all facets of life, and is becoming a game changer in many areas of health care and pharmacy—including in the research and development of many pharmaceuticals.
It’s important that pharmacists pay attention to what’s happening in the industry; after all, as intelligent systems are revolutionize research and development in the pharmaceutical industry, drug discovery and clinical trials are expedited as well.
Machine learning models can sift through vast amounts of biomedical data to identify potential therapeutic targets or predict the efficacy and safety of drug candidates. This acceleration in drug discovery could lead to more effective and personalized medications reaching pharmacies faster. Furthermore, AI can provide pharmacists with updated information about these new drugs, helping them better advise patients.
“Community pharmacists can play a vital role in identifying patients for research trials, as well as considering new regimens with the care team for patients with chronic illnesses,” said Hayley Burgess, PharmD, chief clinical officer at VigiLanz, an EHR clinical surveillance company.
For example, VigiLanz Research uses sophisticated algorithms to review patients against study protocols and identify eligible candidates for clinical trials in real time. These advancements translate to the pharmacy level by offering better-informed and safer medication choices, faster.
Jason Julianois a director within Eisner Advisory Group LLC, who counsels businesses on AI, noted AI can speed up R&D by evaluating massive volumes of scientific literature and clinical data, discovering possible drug candidates, and forecasting their efficacy.
“This enables pharmacists to provide their patients with a broader selection of therapeutic alternatives,” he said. “Predictive models enabled by AI can estimate pharmaceutical efficacy and safety, assisting in individualized therapy selection and dose modifications. These developments allow pharmacists to provide more targeted and accurate care, resulting in better patient outcomes.”
Early drug development has already been influenced by AI. Researchers are leveraging AI to evaluate and “rule in” or “rule out” new molecular entities for consideration in early-phase clinical trials by screening thousands of molecules for how they interact with target proteins.
Reema Hammoud, PharmD, AVP of clinical pharmacy at Sedgwick, a global provider of technology-enabled risk, benefits and integrated business solutions, noted on the R&D side, AI has helped with analyzing data in real time and speeding up the clinical trial process.
“One of the biggest reasons why medications are so expensive is because of the extensive amount of research and time that goes into development,” she said. “AI can analyze data from pre-clinical and clinical studies to identify trends to aid with future development.”
AI can also identify targeted areas of the body in which medication can help. This not only assists with discovery, but can also help to design safer clinical trials, as pre-existing data is informing the development process.
Additionally, Natural Language Processing (NLP) can assist with processing unstructured data in clinical trials, to make the information more digestible to analyze.
Superintendent pharmacist Abbas Kanani, MRPharmS, notes today’s researchers can develop medications that target specific molecular pathways thanks to AI algorithms analyzing genomic data, disease mechanisms and protein structures to identify and validate new drug targets.
“Pharmacies can then provide patients with targeted treatments tailored to their individual needs,” he says. “Pharmacies can also stay updated on potential risks associated with specific medications, enabling them to provide informed counselling and monitoring to patients because of the extensive databases analyzed to identify safety signals and adverse drug reactions, that may not have been detected during clinical trials.”
“Ultimately, AI can help to fast-track and streamline research and development, which leads to improved patient outcomes and lowered medication costs,” Hammoud said.
It is of course important to consider the potential bias that surrounds AI in R&D. AI only knows what it is provided with and collected data from previous trials might not always be applicable to every patient, depending on which population sets it is collected from. However, as AI continues to evolve and get more information from clinical trials, it will only become a stronger tool for R&D.
There’s no question that AI is revolutionizing R&D in the pharmaceutical industry. It’s being used to predict the effectiveness of drugs, identify potential side effects, and even design new drugs.
As these improvements trickle down, pharmacies can expect to see more effective medications, a wider range of treatment options, and potentially quicker time-to-market for new drugs. This leads to better patient outcomes and more informed pharmacists.