Traditional pharma marketing, heavily reliant on science and data, can be improved by adopting consumer goods principles. This involves focusing on simplicity, message consistency, and tapping into emotional insights to cut through a cluttered and competitive marketplace.

Despite sound science, many recent drug launches are failing. The root cause is not the data but an underinvestment in market conditioning. Cautious investors and tighter budgets mean companies are starting their educational and scientific storytelling efforts too late, failing to prepare the market adequately.

The pharmaceutical industry is often misunderstood because it communicates through faceless corporate entities. It could learn from tech's "go direct" strategy, where leaders tell compelling stories. Highlighting the scientists and patient journeys behind breakthroughs could dramatically improve public perception and appreciation.

Pharmaceutical advertising is the second leading source of health information for patients. AI can “de-criminalize” it by moving from untrackable broadcast ads to programmatic, personalized, and compliant digital content, turning it into a valuable and trusted patient resource monitored by the government.

The requirement for prescriptions for many safe drugs stems from a paternalistic medical culture that distrusts patients, not from genuine safety concerns. This drives up costs and creates unnecessary barriers, similar to how the establishment initially resisted home pregnancy and COVID tests.

Eli Lilly and Novo Nordisk's DTC programs for weight loss drugs give employers an alternative to point employees towards, providing cover to drop expensive insurance coverage and potentially reducing access for patients who rely on it.

Pharmaceutical companies have long used Closed Loop Marketing (CLM) to gather physician feedback during sales calls. However, this data often becomes a wasted opportunity. The critical failure occurs when marketing teams receive these insights but do not act upon them to refine content and strategy, rendering the data collection pointless.

When patient engagement is owned by a single department, it's often treated as optional. To make it a core business driver, responsibility must be shared across R&D, medical, regulatory, and commercial teams. This requires a structural and cultural shift to become truly transformational for the organization.

The primary barrier to successful AI implementation in pharma isn't technical; it's cultural. Scientists' inherent skepticism and resistance to new workflows lead to brilliant AI tools going unused. Overcoming this requires building 'informed trust' and effective change management.