Patient engagement drives clinical and commercial success

The past half-decade has ushered in a period of high-velocity innovation in life sciences. At the start of 2020, few outside of specialised circles had heard of mRNA vaccines, GLP-1 receptor agonists, or CRISPR-based therapies. These therapeutic categories have not only been making headlines in 2026; they are fundamentally reshaping both clinical practice and commercial strategy across the industry.

Yet, even the most groundbreaking therapies remain subject to the realities of human behaviour. Realising the full promise of these innovations, whether measured in improved health outcomes or commercial success, depends on people: volunteers who enrol in clinical trials, participants who adhere to study protocols, providers who prescribe new treatments, and patients who follow through with their therapies. As the cost and novelty of new therapies rise, so too do the barriers to participation and adherence at every stage. Patient engagement, therefore, is more critical than ever and requires the same level of innovation as the therapies themselves.

To accelerate patient engagement at the pace required to support clinical innovation, life sciences companies should draw on three key ingredients: behavioural science, patient centricity, and artificial intelligence (AI). Engagement solutions leveraging these three pillars can tap into long-lasting patient motivations that sustain behaviour, even in rapidly shifting contexts. Here’s how.

Supporting patient motivation and context

It’s tempting to think that patients will act if they understand the benefits. Whether it’s the upside of clinical trial participation or the health improvements associated with medication adherence, experts assume education alone is enough to create behaviour change. Yet, people still smoke cigarettes despite clear warnings and skip anti-hypertensive medications even with educational interventions. When patients disengage with therapy, their reasons may have to do with factors that education can’t resolve, such as cost, side effects, or stigma. However, connecting with a patient’s motivation – their desire to engage with a behaviour and achieve a goal – can help empower them to find ways to overcome their barriers to change.

This is where behavioural science comes in. Behavioural scientists design experiences that align with what motivates people, such as values and identities that remain fairly stable over the life span. People are more likely to sustain behaviours when they can see the alignment with what matters to them. For example, a review of shared decision-making in health treatments suggests that patients who actively participate in treatment choices feel the resulting regimen is more aligned with their values, which in turn leads to greater commitment.

Bringing the patient voice into therapeutic development

In late 2025, the US Food and Drug Administration (FDA) unveiled guidance on patient-focused drug development (PFDD), emphasising gathering patient input into drug development, focusing on what matters to patients, and measuring and using outcomes that are fit-for-purpose. The intention of PFDD is to bring patient and caregiver perspectives into product development and regulatory processes, ultimately resulting in more suitable and successful therapies.

While designing methods to collect patient data appropriately takes time and expertise, it can pay dividends in terms of outcomes. For example, public involvement in clinical trial recruitment boosts enrolments, while aligning chronic condition treatments to expressed patient preferences is associated with better adherence. Front-loading the patient voice into the therapeutic development process can help proactively address needs before they become barriers, while also adhering to the latest FDA guidance.

Adapting engagement tactics with artificial intelligence

While people’s values and identities shift slowly, their barriers to action may change quickly. For example, someone new to GLP-1 therapy may grapple with self-injection, while a more seasoned patient may experience barriers to ongoing access or disappointment in the pace of results. To empower people over the course of a therapeutic journey from initiation through maintenance or discontinuation, any engagement strategy must flex and adapt to their changing needs. Enter artificial intelligence (AI).

AI is adaptive by design. Techniques such as reinforcement learning are trained on data indicating patient engagement (or lack thereof), such as interactions with outreach, obtaining and filling prescriptions, and using connected devices. When used to nudge patient behaviour, AI can quickly identify signals to select the right content, timing, and channel to drive action for each individual. This allows an approach that’s both scalable and highly personalised.

Moving at the speed of motivation

With high-velocity therapeutic categories, speed matters. It’s not just about bringing a product to market, but also about optimising it against competitors to meet patient needs and preferences. And the most successful therapeutic products, ultimately, are the ones that people adhere to over time. That’s why combining AI and behavioural science with a healthy dose of the patient voice is a winning strategy. As regulatory frameworks like PFDD and market pressures converge, the winners in high-velocity categories will be those who learn and adapt fastest, at the individual patient level.

About the author

Amy Bucher, PhD, is a nationally recognised leader in using behavioural design to improve health outcomes. She currently serves as the chief behavioural officer at Lirio, where she leads the company’s behavioural science strategy, directing a multidisciplinary team of researchers, designers, and creatives to develop interventions that drive meaningful behavioural change in healthcare. In this role, she also serves as the co-director of Lirio’s Behavioral Reinforcement Learning Lab (BReLL), which brings together experts in behavioural science and AI to advance evidence-based, personalised approaches to behaviour change. Prior to joining Liroi, Bucher held leadership roles at CVS Health, Johnson & Johnson Health & Wellness Solutions, and Mad*Pow. She is the author of “Engaged: Designing for Behavior Change”, a comprehensive guide for research, design, and UX professionals seeking to apply behavioural science in the digital health setting.