Healthcare
Improving patient care and safety with AI
Few technology advancements hold as much promise and potential as artificial intelligence (AI) in healthcare. This transformative technology is reshaping traditional healthcare practices while revolutionising the pharmaceutical industry, which is the backbone of healthcare. AI is becoming a pivotal force, driving efficiencies, improving patient care and paving the way for many enhanced outcomes. From drug discovery and precision medicine to enabling cost-effective accessibility, AI is streamlining processes and opening up frontiers previously unimaginable. A McKinsey study estimated that ‘Gen AI could generate $60 billion to $110 billion a year in economic value’ across the pharmaceutical industry value chain. So, what does AI in pharmacy entail? Let us explore.
AI in pharmacy
Speed and precision are two crucial aspects of the pharmaceutical industry. AI emerges as a game-changer for these aspects, impacting multiple facets of R&D, drug discovery and development and patient outcomes. From analysing complex datasets to making informed predictions and decisions based on patterns and trends, machine learning (ML) algorithms transform tasks that wholly rely on human intelligence. Let’s delve a little deeper into a few aspects of how AI is shaping the future of pharmacy.
Applications of AI in pharmacy
- Drug discovery and development
- Precision medicine
- Medication management
- Patient communication
- Patient outcomes
AI, specifically Gen AI, is revolutionising this key pharmacy aspect by accelerating various critical processes. In R&D, AI helps generate molecules faster with enhanced safety, quality and novelty, augmenting the development of drugs, especially vaccines. In clinical trials, AI helps improve patient matching, predicts drug interactions and bioactivity, and improves the chances of success. AI algorithms run through vast troves of patient data to study demographics, genetic profiles and medical histories to arrive at suitable candidates for clinical trials. The McKinsey study pegs up to 50 per cent cost reductions through streamlined clinical trial processes with a 12-plus month acceleration in the time to conduct trials. There is also a 10 per cent increase in the possibility of success for trials.
AI guides research scientists on drug developments for cancer, multiple sclerosis (MS) and other rare diseases. It finds several patterns in enormous datasets and provides valuable insights. Whether exploring vast chemical spaces efficiently or offering insights into complex biological interactions, AI fosters efficient R&D. It optimises R&D pipelines, making them robust against setbacks by predicting or detecting early failures. Additionally, AI can catalyse polypharmacology to help map relationships between drugs, genes and diseases to test candidates for drug repurposing. It helps find new therapeutic uses based on their molecular properties and biological interactions, bringing costs down significantly. These aspects accelerate the regulatory approval process to take the drugs into the market faster.
AI is taking precision medicine to the next level by helping researchers use biomarkers to categorise patients based on disease progression predictions. It also helps them understand why certain groups respond in a way to certain medicines. From experimenting with a controllable ingestible origami robot for wound patching to possibilities of mass-customised generics of precision dosing being made available in the market, the possibilities are endless. Also, precision medicine will change chronic disease management by personalising treatment significantly.
Tracking patient profiles and changing prescriptions, understanding drug interactions, dosage adjustments and associated instructions, and managing therapies and counselling are key medication management challenges. AI-powered systems are helping pharmacists manage these complex tasks without errors for enhanced patient safety. It also helps monitor patients’ adherence to prescribed medications with reduced risk of missed doses or adverse drug interactions.
AI-powered systems can improve patient communication in multiple ways. AI chatbots and virtual assistants can help educate patients on disease and medication management to improve adherence, allay fears and reduce clinic visits. Reminders and monitoring alerts vastly increase the effectiveness of patient communication with timely engagements. Chatbots can help patients with prescription refills or renewal requests, freeing up pharmacists and reducing wait times. It leads to enhanced patient satisfaction.
AI helps strengthen the core aim of the pharmacy industry, which is ensuring better patient care and outcomes. Pharmacy automation leads to streamlined workflows for better coordination between all stakeholders. An efficient EHR integration can provide real-time patient information to ensure proper care. It also streamlines claims processing and reduces the risks of medication errors.
Predictive data analytics is another AI aspect that has the potential to enhance patient outcomes significantly. Trends and patterns from the patient data can provide valuable insights for better decision-making.
AI in pharmacy is heralding changes from the old-world pharmacy systems that relied on people and manual processes to more efficient automated systems and personalised patient care with improved outcomes. AI will transform the future of pharmacy by delivering faster, safer and cheaper drugs. It helps the industry move towards value-centric R&D, build more resilient supply chains and boost digital pharma manufacturing.
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