This post originally appeared on Fast Data Science’s blog on LinkedIn.
Budgeting is one of the most critical steps when planning a clinical trial. Clinical trials are complex, multi-phase studies that require significant resources, and understanding the costs associated with each phase is crucial for an accurate clinical trial budget. In this post, we’ll explore the different phases of clinical trials and the key factors that influence their costs, providing insights into how to prepare a comprehensive budget that aligns with your trial’s needs.
Clinical trials progress through phases, each serving a specific purpose, lasting a particular duration, and carrying distinct cost implications. Let’s break down the cost for each phase:
Phase 1 Trials: These trials are designed to assess a drug’s safety and typically involve a small sample of 15-20 participants. The average cost of a Phase 1 clinical trial is around $4 million.
Phase 2 Trials: The drug’s efficacy is tested, often with a larger group of participants. The costs rise considerably, with Phase 2 trials averaging $13 million.
Phase 3 Trials: These pivotal studies involve hundreds or thousands of patients and aim to confirm the drug’s effectiveness across a large, diverse population. They are the most expensive, averaging $20 million or more.
Pivotal Trials: Some pivotal Phase 3 trials, particularly those required for FDA approval, may cost a median of $41,117 per patient.
Each phase of a clinical trial carries its own financial demands, and it is important to allocate funds accordingly based on the trial’s scope.
Aylin Sertkaya and colleagues from Eastern Research Group, Inc., provided these cost estimates in a report submitted to the U.S. Department of Health and Human Services.
The cost of a clinical trial does not solely depend on the phase. Several factors significantly influence the overall budget, making it essential to account for these when planning your clinical trial budget:
Study Size and Recruitment
Geographical Scope
Therapeutic Area
Trial Complexity
Duration and Timeline
Commercial vs. Academic Trials
When preparing your clinical trial budget, it’s vital to forecast the expenses based on the factors outlined above. Here are some key considerations to ensure an accurate budget:
Accurately Estimate Costs by Phase: Start by understanding the average costs of each clinical trial phase and ensure your budget reflects these costs.
Forecast Recruitment and Site Costs: Ensure your budget accounts for the number of patients you plan to recruit and the number of sites involved. Remember to underestimate the costs of recruitment, as slow recruitment can lead to additional infrastructure costs.
Account for Trial Complexity: Trials that involve personalised treatments, rare diseases, or advanced procedures may require more specialised staff, equipment, and longer monitoring periods, which can increase the costs.
Include Regulatory and Logistical Costs: Ensure that your budget includes regulatory submissions, monitoring visits, data management, and patient follow-up costs, which vary depending on the number of countries and sites involved.
Plan for Hidden Costs: Always include a contingency for unexpected costs, such as protocol amendments, regulatory changes, or patient attrition.
Understanding the phases of clinical trials and the factors influencing costs is essential for preparing an accurate clinical trial budget. By taking into account study size, geographical scope, therapeutic area, and trial complexity, you can develop a budget that reflects your study’s true scope and requirements. Accurate budgeting ensures the trial runs smoothly and maximises the likelihood of achieving its objectives within the available resources.
Whether you are conducting an industry-sponsored trial or an academic study, careful financial planning is the key to success in clinical research.
Looking for accurate cost estimates for your clinical trial? Fast Data Science specialises in providing AI-driven solutions to optimise clinical trial budgets. Get in touch with us today!
Additional Reference:
JAMA Intern Med. 2018;178(11):1451-1457. doi:10.1001/jamainternmed.2018.3931
Guest post by Safeer Khan, Lecturer at Department of Pharmaceutical Sciences, Government College University, Lahore, Pakistan Introduction The success of a clinical trial is strongly dependent on the structure and coordination of the teams managing it. Given the high stakes and significant impact of every decision made during the trial, it is essential for each team member to collaborate efficiently in order to meet strict deadlines, comply with regulations, and ensure reliable results.
Guest post by Youssef Soliman, medical student at Assiut University and biostatistician Clinical trial protocols are detailed master-plans of a study – often 100–200 pages long – outlining objectives, design, procedures, eligibility and analysis. Reading them cover-to-cover can be daunting and time-consuming. Yet careful review is essential. Protocols are the “backbone” of good research, ensuring trials are safe for participants and scientifically valid [1]. Fortunately, there are systematic strategies to speed up review and keep it objective.
Introduction People have asked us often, how was the Clinical Trial Risk Tool trained? Does it just throw documents into ChatGPT? Or conversely, is it just an expert system, where we have painstakingly crafted keyword matching rules to look for important snippets of information in unstructured documents? Most of the tool is built using machine learning techniques. We either hand-annotated training data, or took training data from public sources. How We Trained the Models inside the Clinical Trial Risk Tool The different models inside the Clinical Trial Risk tool have been trained on real data, mostly taken from clinical trial repositories such as clinicaltrials.
