Fraught with risk yet pivotal to the future success of a drug candidate, clinical trials are undeniably a high-stakes endeavour. All being well, the process will be completed as quickly as possible, the time-to-market opportunity maximised, and the investment can be kept to a minimum. But suppose there are friction points along the pathway. In that case, however, there is potential for extended time frames and additional expense, with estimates ranging from $600,000 to $8 million per day of delay depending on the market opportunity of the drug candidate and, of course, as the end date of premium pricing is fixed, time is of essence to maximise the opportunity before generic alternatives become available.
There are several activities that contribute towards clinical trial budgets; from a general standpoint, these costs include per-patient costs (such as patient recruitment and retention), study site costs (such as investigator fees, site staff / administrative fees, IRB fees, procedure fees), and per-study fees (such as data collection fees, monitoring, sponsor / CRO personnel salaries, protocol amendment fees, and vendor costs). However, aside from the fact that study timeline slippage unexpectedly expands study budgetary forecasts, timeline slippage also results in a $600,000 per day in lost revenue opportunity for niche products, and up to $8 Million per day for blockbuster medical products.
It would be ideal if all patients adhered to the investigational medical product (IMP) and the study protocol, nonetheless, many patients do not. Approximately 40% of patients become non-adherent to IMP after 150 days in a clinical trial, which not only causes temporary bouts of toxicity (double dosing) and lack of efficacy (skipping doses), but also introduces data variability into the equation.
Increases in data variability means that study teams need to enroll more patients in order to achieve the study’s statistical outcomes. It is important to emphasise that linear increases in non-adherence have an exponential impact on the number of patients needed to yield the same statistical outcome. To demonstrate, a 20%-30% IMP non-adherence rate requires a 50% increase in the study’s sample size in order to maintain equivalent statistical power; once non-adherence increases to 50%, the trial sample size needs to increase by 200% in order to maintain equivalent statistical power. Yet, discussion amongst industry professionals on the topic suggests that study scientists do not factor patient non-adherence in trial design.
Patient nonadherence leads to enrolling more patients to achieve the same statistical outcomes, increases study timeline slippage, and subsequently, elevates operational costs. On average in all therapeutic indications, a Phase III trial needs to enrol an additional 460 patients (totalling 828 patients) in order to maintain equivalent statistical power, assuming a constant 40% IMP non-adherence rate. The operational cost to enrol 460 patients is estimated at $12 Million. By reducing IMP non-adherence by 1% (to 39%), sponsors need to enrol 13 less patients in order to maintain equivalent statistical power, resulting in approximately $336K in cost savings, and naturally, minimising timeline slippage.
This analysis shows only one case of study non-adherence (IMP non-adherence), which has a direct impact on data variability and statistical outcomes. When combined with other forms of clinical trial non-adherence (i.e., subject dropout, not completing ePRO questionnaires, missing study visits, and not adhering to study procedures, etc.), further study prolongation is imminent.
Participants must follow the prescribed protocol in patient adherence clinical trials for the outcome to be reliable. Patient adherence directly affects data integrity and influences the validity of study conclusions and regulatory approval. Without consistent adherence, even well-designed trials can produce misleading outcomes and compromise the value of research.
Poor adherence is caused by complex dosing schedules, logistical burdens, and lack of patient support, among other factors. Low trial adherence makes efficacy signals harder to detect and leads to inconclusive or inaccurate findings. Patient adherence clinical trials are strengthened by practical interventions that mitigate deviations and produce results that reflect their true efficacy
Adherence is influenced by study complexity, patient engagement, and external pressures. Participants struggling with complicated medication regimens or frequent site visits may unintentionally deviate from the protocol. Some may forget doses, while others discontinue treatment due to side effects, lack of perceived benefit, or external stress.
Financial, logistical, and psychological burdens also affect adherence. Trials that don’t consider these realities see high dropout rates or non-compliance, their statistical power is reduced, and their treatment effects are distorted. Clear communication, simplified study requirements, and patient support improve engagement and retention.
Education is key. Patients who understand the importance of adherence and how it impacts both their outcomes and broader study findings are more likely to stay compliant. Transparent discussions about expectations, risks, and benefits create a sense of partnership between researchers and participants, fostering greater commitment to trial protocols.
Adherence is also influenced by how well patients connect with trial staff. A supportive research team that prioritises clear, empathetic communication fosters better relationships with participants. Patients who feel heard and respected are more likely to engage consistently with study requirements. This makes ongoing engagement strategies essential, including regular check-ins and personalised support plans.
Effective adherence monitoring requires a combination of technology, direct patient interaction, and data analysis. Passive monitoring tools, such as smart pill bottles and digital reminders, provide real-time adherence pattern reports. Electronic patient-reported outcomes (ePROs) show researchers early signs of non-adherence.
Regular visits and remote check-ins are touchpoints for patients to discuss challenges and receive support. A clear picture of compliance combines objective adherence measures with patient feedback. Participants that struggle with adherence can benefit from dose adjustments or additional counselling.
Integrating artificial intelligence (AI) into adherence monitoring is a growing area of interest. AI-driven models can analyse patient-reported data to predict potential adherence risks before they result in non-compliance. By flagging these risks early, trial teams can deploy targeted interventions, helping patients stay on track while reducing data variability.
When adherence is systematically monitored, deviations can be identified and addressed promptly. This proactive approach minimises missing data, enhances study robustness, and improves the reliability of conclusions drawn from trial results.
Patient-friendly trial frameworks reduce adherence challenges. Flexible visit schedules, decentralised trial options, and home-based monitoring alleviate logistical burdens. Transportation assistance or delivery of products further helps patients maintain consistency.
Improving trial adherence is possible through digital engagement tools that keep participants informed and motivated. Mobile apps, automated text reminders, and virtual check-ins reinforce study commitments and accommodate individual needs.
Personalisation enhances the effectiveness of interventions. Some patients benefit from motivational interviewing that identifies barriers and builds commitment and engagement, while others require structured support, such as coaching or simplified medication regimens.
Trial staff have a role in improving trial adherence. With proper training, research teams can respond effectively to participant concerns and improve retention and compliance. Trial teams that actively listen and adapt reduce dropout rates and strengthen study results because patients are more likely to remain engaged.
Patient-centred trial design considers participant lifestyles and minimises unnecessary complexity. Researchers must balance scientific rigour with practical feasibility, ensuring that trials are both methodologically sound and accessible. This approach leads to higher retention rates, better data quality, and ultimately, more meaningful research outcomes.
Adherence is more than a measure of patient compliance—it is essential for generating high-quality data. Inconsistent adherence introduces variability, dilutes treatment effects and complicates data interpretation. When adherence rates drop, the accuracy of study conclusions also decreases, which, in turn, affects regulatory approval and clinical adoption.
A structured adherence strategy enhances trial outcomes by ensuring data integrity. This involves standardising adherence measurement methods across different sites and using consistent reporting frameworks. By reducing variability, researchers can be more confident in their findings, leading to more robust regulatory submissions and clinical recommendations.
Proactively addressing adherence strengthens trial outcomes by reducing data inconsistencies and ensuring that study findings are accurate and generalisable. Investigators who prioritise adherence from study initiation set a foundation for reliable, actionable results. This not only benefits researchers but also improves the likelihood of bringing effective treatments to market.
Adherence strategies should not end with trial completion. Post-trial follow-up studies can provide additional insights into long-term adherence trends and inform future trial designs. Lessons learned from adherence monitoring in one study can enhance best practices for future clinical research.
Keith Berelowitz is the Founder of trialport, a company redefining patient engagement and retention in clinical trials using living experience, proven methods, and AI.