Exploring the Potential of Artificial Intelligence in the Pharmaceutical Industry

As marketers and managers know, the challenges and excitement of pharmaceutical product launches are potentially as profitable for companies as they are beneficial for patients. Nonetheless, careful planning and resourcefulness are instrumental in developing a corporate roadmap for new products. Executing a launch well means that a new pharma product is more likely to become a market leader. Below, we discuss how to achieve success through a sophisticated approach involving influence mapping tools. Read on to discover more, including an overview of today’s leading software systems. Armed with this information, your pharmaceutical company can harness the power of Artificial Intelligence or AI in development projects, product launches and sales campaigns. Facing the challenges The different stages in the path from R&D to product launch frequently involve various teams and functions. Although the groups involved often share similar goals, they tend to operate in a degree of isolation. At each stage, experts address a relatively narrow set of challenges related to their immediate responsibilities. Though the best amongst them will endeavor to consider the broader situation wherever possible, there may sometimes be little incentive to do so. In some cases, short-term conflicts can arise. In contrast, the safe development of effective drugs, medicines and appliances is, of course, multidisciplinary. It involves research and collaboration, combining the efforts of multiple departments – sometimes in different countries. Apart from an in-depth knowledge of the disease area concerned, medical professionals within a company need to remain keenly aware of patient care and stakeholder expectations. Achieving this delicate balance requires thoughtfulness, accurate information, well-developed commercial insight and, of course, interpersonal skills. Making informed decisions Remaining competitive requires the linking of clinical results to patient outcomes. For instance, when customer service and support representatives or teams liaise with healthcare providers, they may well uncover unmet patient needs. A cross-functional approach between commercial, clinical and regulatory elements should also research treatment outcomes, hear input from patient’s representatives and communicate with public and investor relations. Maximizing return on investment Remaining competitive requires the linking of clinical results to patient outcomes. For instance, when customer service and support representatives or teams liaise with healthcare providers, they may well uncover unmet patient needs. Similarly, valuable insights might emerge regarding patient’s acceptance of products, revealing untapped market potential and enabling additional clinical programmed to boost ROI. Using software to align teams Nowadays, a choice of feature-rich software packages has made the latest in Artificial Intelligence (AI) available to the world of pharmaceuticals. Now, it is possible to manage information, answer queries and display reports with ease. Such packages typically boast intuitive and user-driven interfaces to acquire and preserve essential details. Also, powerful algorithms search for connections, log the results and analyzeimplicit knowledge such as key stakeholders and their links. Group knowledge becomes implicit by asking brand teams to share data about accounts via influence maps. Later, colleagues and members of other groups can leverage this information in a productive, cross-team approach. Across the pharma manufacturing sector, cross-functional teams can now benefit from granular and accurate account stakeholder maps, updated in real-time. Significantly, team alignment and influence maps allow pharmaceutical companies to get the most from their team’s relationships with each corporate function and – crucially – with stakeholders. Examples of problems and quirks included: Making influence maps work for you An AI based engines will identify Key Opinion Leaders (KOLs) based on the accumulated data. Pharmaceutical companies have used the influence of highly experienced researchers and physicians to seek out more takers of new drugs and clinical trials. Artificial Intelligence can add more value by quantifying their influence and giving back an elaborate measurement to run a better campaign. Pharma companies can implement Machine Learning for allocating right experts for campaign needs via influencer marketing. For this, AI can be fed number of topics, publications, research produced by such experts and understand their audience. So, there you have it. If you are a business decision-maker or policymaker, you now have an exciting opportunity. Deployed to good effect, the latest influence mapping techniques and AI look set to fuel organic business growth in forward-thinking pharma companies.