Article summary / TLDR
1. Externally controlled trials use pre-existing data from historical clinical trials or real-world data sources to create an 'external control arm' as comparator to evaluate the efficacy and safety of new interventions.
2. This method offers a viable solution to settings where a randomised trial design is not feasible, such as in rare, life-threatening, or severely debilitating conditions.
3. Despite their benefits, externally controlled trials pose significant concerns regarding validity and potential bias due to lack of comparability between treatment and control arm.
4. The FDA therefore recently published guidelines on how to design and conduct externally controlled trials and recent success stories highlight how these type of trials can be used to accelerating treatment evaluation and inform early go/no-go decisions.
The confines of randomised controlled trials
Randomised controlled trials (RCTs), are widely regarded as the “gold standard” in clinical research. Praised for their scientific rigor and statistical robustness, RCTs ensure an unbiased evaluation of efficacy and safety by assigning patients to either a treatment arm or a control arm with placebo or standard of care. By randomly allocation patients to one of these groups, clinical researchers aim to neutralise the effect of any confounding factors stemming from the patient’s diverse clinical experiences and outcomes. This design feature enables researchers to evaluate whether observed outcome differences can truly be attributed to the treatment of interest.
Despite its strengths, executing an RCT can be challenging, particularly when the target patient population is small and hard to find. Depending on study phase, sponsors are often required to recruit hundreds of participants, of which only a part will receive treatment. This is generally regarded as a painstaking task and indeed research shows that 9 out of 10 clinical trials fail to meet their recruitment timeline[1]. Additionally, evidence suggests patients are less willing to participate in placebo-controlled RCTs, further complicating recruitment and retention[2].
Fortunately, recent advancements in data science and technology offer a possible solution for cases where RCTs are simply not feasible. By drawing from the ever-growing pool of data sources beyond traditional clinical trials, sponsors can generate an external control arm (ECA), also called a ‘virtual’ or ‘synthetic’ control arm. This new method promises to unlock a next wave of innovation in treatments that target rare and life-threatening disease as well as precision medicine. In this article, we’ll unpack both the promises and limitations of this innovative approach, covering key benefits, design considerations, implementation challenges, and notable success stories.
Introducing externally controlled trials
Externally controlled trials use pre-existing data as a comparator to evaluate the efficacy and safety of new interventions, instead of depending solely on a concurrent control arm. This approach provides a solution to clinical trial settings where recruiting a control arm is not feasible or ethical, such as in rare, life-threatening, or severely debilitating conditions with no or inadequate treatment options.
An externally controlled trial draws patient-level data from historical clinical trials or real-world data (RWD) sources, such as electronic health records (EHRs), registries, or medical claims. For an ECA to be valid, the data compilation and patient selection criteria must match and closely resemble the clinical trial under investigation. Sponsors should therefore take adequate measures to ensure treatment and control arm are as comparable as possible to mitigate potential bias and confounding factors.
In practice, ECAs can enhance and support both single-arm trials and RCTs. When applied appropriately, they can offer critical insights throughout all stages of clinical development—from early go/no-go decisions to final approvals and regulatory submissions. Let’s dive into some of the key benefits of this novel methodology.
The benefits of the external control arm
Externally controlled trials bring a number of benefits to modern clinical trial design and conduct (see Figure 1). First, ECAs can drastically reduce the number of clinical trial participants that need to be recruited. It is estimated that an ECA can lower patient recruitment needs by 20-50%[3]. Given that the average cost per patient is $40k[4] and clinical trials typically recruit between 65 patients (Phase 1) and 638 patients (Phase 3)[5], cost-savings can range into the millions.
Besides saving on the resources needed for recruiting and managing control arm participants, a lower recruitment target also accelerates the recruitment process. This alleviates a major bottleneck for clinical trial sponsors, especially those focusing on treatments for rare diseases where the patient population is small and hard to come by. For patients, externally controlled trials are also more appealing because they have a higher change of receiving treatment as rather than placebo or standard of care, thus potentially providing a further boost to recruitment.
With these cost and time-saving benefits, externally controlled trials show much promise for accelerating the evaluation of novel treatments, especially in rapidly evolving fields such as oncology. Furthermore, sponsors can use an ECA for generating preliminary insights into the potential efficacy and safety of their intervention—insights crucial for planning and guiding further research and determining whether a more rigorous RCT is needed.
Lastly, externally controlled trials bring ethical benefits since they minimise the number of patients that will receive a placebo or standard-of-care treatment that may be less effective. This is particularly relevant when new evidence suggests the investigational treatment is beneficial.
Design considerations & challenges
Despite their potential, externally controlled trials can pose significant concerns regarding validity and potential bias. The primary challenge here is ensuring that treatment and control arm are as similar as possible, accounting for both known and unknown factors that can affect the outcome being measured. To address this challenge, the FDA recently published draft guidance on key considerations for the design and conduct of externally controlled trials, including how to communicate and submit these studies to FDA officials[6].
The FDA guideline emphasises that the suitability of an ECA must be evaluated on a case-by-case basis and is highly dependent on key factors such as the heterogeneity of the disease, any preliminary evidence on the investigative treatment, and the methods used to assess the outcome of interest. Sponsors should investigate whether it is possible to distinguish treatment effect from outcomes that can be attributed to the disease’s natural history, prognostic differences in the study population, lack of blinding, or other factors such as differences in concomitant therapies. For instance, externally controlled trials are not suitable for cases where the natural history of a disease is poorly understood or where the disease is known to improve in the absence of intervention or with standard of care.
In terms of timing, it is crucial that sponsors do not initiate an ECA after completion of a single-arm trial, but rather start this process after finalising the study protocol. This ensures the protocol pre-defines all critical ECA design elements such as suitable data sources, baseline eligibility criteria, appropriate exposure definitions and windows, well-defined and clinically meaningful endpoints, cogent analytic plans, and approaches to minimise missing data and sources of bias.
As mentioned, a key hurdle for externally controlled trials is the variability of external data and its fitness for use. Variations in study design, patient population, or treatment standards may undermine the comparability between treatment and control arm, resulting in biased observations. Furthermore, the FDA highlights the potential impact of disparities in healthcare outcomes due to variability in population demographics, socio-economic factors, and healthcare systems across different regions and time periods.
Variability concerns extend to both historical clinical trial data and RWD, with the latter requiring even more caution duet o a higher incidence of missing and misclassified data. For instance, EHRs from routine clinical care may include information on lifestyle characteristics, such as alcohol use, where healthcare providers may use different quantitative or qualitative descriptions. Consequently, two patients with a similar alcohol intake may be assigned to different categories, posing a serious problem if alcohol use is a critical confounding factor (covariate) in the analysis of treatment effect.
To address this issue, the FDA guidelines offer a comprehensive overview of critical factors to consider when assessing data comparability between treatment and control arm (see Table 1). This overview supports sponsors in their endeavour of finding comparable data and in proactively managing potential validity threats to their trials.
Communicating with regulators
Given the novelty of this approach, regulatory requirements are still diverse and evolving. This was confirmed by a research study which concluded that regulatory acceptance of identical package varied across jurisdictions[7]. Sponsors are therefore recommended to keep an ongoing dialogue and consultation with applicable regulators. The FDA recommends sponsors to consult with the relevant FDA review division early in their drug development program to assess the feasibility of incorporating an ECA.
During these consultations, sponsors are expected to provide a detailed description of the (1) reasons why the proposed study design is appropriate, (2) proposed data sources for the ECA and an explanation of why these are fit for use, (3) planned statistical analyses, and (4) plans to address FDA’s expectations for the submission of data.
Real-world applications: Case studies & success stories
While ECAs have frequently been employed to establish natural history of disease[8], their use for generating primary evidence is yet to pick up pace. At the time of writing, only a handful of success stories exist which, though limited in number, clearly demonstrate potential and regulatory openness to externally controlled trials.
One company that is spearheading the use of ECAs is Medicenna, which recently received FDA approval to design a Phase 3 study that combines both a concurrent control arm and ECA to evaluate its drug MDNA55 for recurrent glioblastoma multiforme (rGMB). The approval was granted after Medicenna successfully conducted a Phase 2 study that included an ECA with patients from rGMB registries going back 5 years. This Phase 2 study marked the first-ever registration trial approved by the FDA that included an ECA, applying the same inclusion/exclusion criteria in both the treatment and control arm by looking at 11 different prognostic factors such as age, tumour size, tumour location, and genetic makeup of the tumour[9].
Another case study involves biopharma company Imunon, which compared data from a Phase 1B study on its advanced ovarian cancer drug IMNN-001 (formerly GEN-1) with historical clinical trial patients who received standard neoadjuvant chemotherapy. The preliminary findings on IMNN-01’s potential comparative treatment advantage over standard of care informed the decision to continue its clinical development under the FDA’s Fast Track designation while also providing practical information on study design, including the appropriate number of patients to recruit for the subsequent phase 2 study[10].
Historical clinical trial data or RWD?
Externally controlled trials utilise patient-level data from historical clinical trials or RWD sources (e.g., EHRs, registries, etc.). Here, clinical trial data is generally regarded to be more rigorous, robust, and complete compared to RWD. For example, clinical trial protocols generally include a plan for collecting data on concomitant medications that could impact the observed outcomes, including detailed data on the characteristics and administration of such medications. In contrast, such data is more likely to be unavailable, incomplete, or inaccurate in RWD collected during routine clinical care.
Introducing the Clinical Insights Exchange
Triall is building the Clinical Insights Exchange (CIX), a platform that enables analysis of historical clinical trial data to inform future research in its planning and design. The CIX platform applies advanced cryptographic techniques such as Compute-to-Data to allow for privacy-friendly analysis over aggregated data from clinical datasets and eClinical systems connected to the platform. It therefore enables biopharma companies, clinical CROs, and medical research institutes to provide and consume clinical trial data without compromising data privacy or confidentiality. This allows these companies to generate data-informed insights that promote the speed, resource-efficiency, and predictability of their clinical development activities.
Future outlook: Where do we go from here?
Externally controlled trials will undoubtably play an important role in the future clinical trial arena. Today’s success stories demonstrate how both external and hybrid control designs can accelerate the evaluation of new treatments as well as inform early go/no-go decision moments that guide further research. As clinical trials evolve to become more digital, data-driven, and patient-centric, ECAs are likely to gain a strong foothold with sponsors and regulators alike. Ongoing dialogue, capacity-building, and the development of robust guidelines are essential for navigating the challenges and realising the full potential of this innovative approach.
References
- MIT Technology Review Insights (2021). Clinical trials are better, faster, cheaper with big data.
- Groth, S. W. (2010). Honorarium or coercion: use of incentives for participants in clinical research. The Journal of the New York State Nurses' Association, 41(1), 11.
- Boston Consulting Group (2021). Transforming clinical trials with real-world evidence.
- Moore, et al. (2018) Estimated Costs of Pivotal Trials for Novel Therapeutic Agents Approved by the US Food and Drug Administration, 2015-2016. JAMA International Medicine.
- Statista (2022). Average number of subjects per clinical drug trial started worldwide from 2015 to 2020, by trial phase.
- FDA (2023). Considerations for the design and conduct of externally controlled trials for drug and biological products: Guidance for industry.
- Sola‐Morales, O., Curtis, L. H., Heidt, J., Walsh, L., Casso, D., Oliveria, S., ... & Quek, R. G. (2023). Effectively leveraging rwd for external controls: A systematic literature review of regulatory & hta decisions. Clinical Pharmacology & Therapeutics.
- Jahanshahi, M., Gregg, K., Davis, G., Ndu, A., Miller, V., Vockley, J., ... & Sakai, S. (2021). The use of external controls in FDA regulatory decision making. Therapeutic Innovation & Regulatory Science, 55(5), 1019-1035.
- Ed Miseta (2021). How An External Control Arm Changed Phase 3 Trials For Brain Cancer. Clinical Leader.
- Yin, X., Davi, R., Lamont, E. B., Thaker, P. H., Bradley, W. H., Leath III, C. A., ... & Borys, N. (2023). Historic Clinical Trial External Control Arm Provides Actionable GEN-1 Efficacy Estimate Before a Randomized Trial. JCO Clinical Cancer Informatics, 7, e2200103.
