Randomised controlled trials (RCTs) are often costly, slow, and logistically challenging - ChatGPT (2025)

In this article, we asked ChatGPT to provide a better solution for randomised controlled trials (RCTs). Here's what ChatGPT said:

You're absolutely right—randomised controlled trials (RCTs), while considered the gold standard for evidence, are often costly, slow, and logistically challenging. Here are some pragmatic, more feasible alternatives or complementary approaches that can provide valuable evidence—especially in real-world settings or for repurposed/low-cost interventions:

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✅ 1. Pragmatic Clinical Trials (PCTs)

• What: Conducted in real-world settings with broad patient inclusion criteria.

• Advantage: Less strict protocol than traditional RCTs, more generalisable, lower cost.

• Use Case: E.g., testing off-label or repurposed drugs like ivermectin or fenbendazole in actual outpatient settings.

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✅ 2. N-of-1 Trials

• What: A single patient undergoes multiple treatment periods with different therapies in random order.

• Advantage: Useful for rare diseases or personalised treatment; faster and cheaper than large trials.

• Use Case: Individualised testing for patients unresponsive to standard cancer therapies.

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✅ 3. Synthetic Control Arms

• What: Use historical data or real-world evidence (RWE) to replace or supplement the control group.

• Advantage: Reduces need to randomise patients to placebo; saves time, money, and ethical concerns.

• Use Case: Oncology studies where standard-of-care is already well documented.

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✅ 4. Real-World Evidence (RWE) from Observational Studies

• What: Retrospective or prospective cohorts using EMRs, patient registries, claims data, etc.

• Advantage: Large, inexpensive data sets reflecting everyday practice; valuable especially when RCTs are not feasible.

• Use Case: Evaluating long-term effects or safety profiles of interventions already in use.

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✅ 5. Case Series / Retrospective Case Reviews

• What: Compile and analyse existing anecdotal or clinical case data.

• Advantage: Fast, useful for hypothesis generation or rare outcomes.

• Use Case: Early-stage evaluation of repurposed or natural treatments in cancer (e.g. fenbendazole and ivermectin projects).

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✅ 6. Bayesian Adaptive Trials

• What: Uses Bayesian statistics to continuously update probability of treatment effect as data accumulates.

• Advantage: More efficient, allows for early stopping or arm-dropping; flexible.

• Use Case: Small-scale oncology studies where multiple treatment arms are tested.

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✅ 7. Digital Trials / Remote Monitoring

• What: Use apps, wearables, and telemedicine to gather patient-reported outcomes and data.

• Advantage: Reduces infrastructure cost, improves scalability, improves compliance.

• Use Case: Lifestyle or dietary interventions; long-term safety/effectiveness follow-ups.

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🔁 Hybrid Strategy Recommendation:

For controversial or off-label interventions (e.g. repurposed drugs, supplements), a retrospective case series → matched cohort from real-world data → pragmatic or adaptive trial pathway offers progressive evidence-building without jumping straight into a multi-million dollar RCT.

Source: https://chatgpt.com/share/68591d9a-ce0c-8006-8ec6-d14b58470b10