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10 Things You Should Consider When Planning a COVID-19 Clinical Drug Trial

By Rajesh Krishna, PhD

Pandemics by nature are excellent fodders for disruptive innovation. They force you to think out of the box. The whole health care apparatus is on the COVID-19 frontlines with some more directly involved than others. If you are a scientist or a clinician researcher at a biotech company or an academic laboratory, you are likely thinking, “how can I made a real impact in saving human lives?” You might find credible ways to contribute to advancing human health. The answer might be literally sitting on your shelf! Craig Rayner and team exemplify these behaviors in a seminal commentary on innovating by thinking without borders.

Rayner CR, Smith PF, Hershberger K, Wesche D. Optimizing COVID-19 Candidate Therapeutics: Thinking Without Borders. Clin Transl Sci. 2020 Mar 25. doi: 10.1111/cts.12790.

Here are the 10 questions you should consider if you have a molecule in development or an idea about a drug already in clinical use.

1. Does my candidate drug have potential efficacy in COVID-19 patients?
This is by far the most important first step. Right now, you might think, “oh wow, we are throwing everything but the kitchen sink at this virus hoping something might work.” Well, this is one approach, but this empirical strategy could end up wasting valuable resources with little return.

Innovation happens incrementally. Such is the story of Apple handheld devices, for example, and the continuous innovation with each version. Similarly, in approaching therapeutics for COVID-19, the idea is to learn from each step. The more prudent way is to understand how your drug works, and whether there is anything in the emerging biology of coronavirus that makes your drug worth studying. Look at how your drug works, at proximal markers of target engagement and any distal downstream biomarkers. The continuum of pharmacology may offer interesting clues on how your compound could work and in what ways.

2. Does my drug inhibit SARS-CoV-2 and if so, at what concentrations?
Once you have evidence that your drug might work but are not sure of its mechanism of action, i.e., whether the drug directly effects the virus or affects something in the downstream pharmacology, the next step is to run a cell-based incubation in vitro test in SARS-CoV-2 isolates. That test would yield the inhibitory concentration values (or the IC50 value) of your drug. This helps you understand two things, one, whether by extrapolation you can achieve clinically equivalent concentrations to test your concept in humans, and two, to get an idea whether your drug has a direct effect. A good example is the work of Yao and coworkers in identifying the IC50 of hydroxychloroquine.

Yao X, Ye F, Zhang M, et al. In vitro antiviral activity and projection of optimized dosing design of hydroxychloroquine for the treatment of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). Clin Infect Dis. 2020;pii: ciaa237. https://doi.org/10.1093/cid/ciaa237 [Epub ahead of print]

3. Can I translate my in vitro findings to human drug effect?
While in vitro activity is helpful, it represents an artificial system wherein the virus is directly exposed to the drug. From our learnings in oncology and neuroscience, translatability into human beings is governed by many different factors including, the ability of the drug to reach its site of action at meaningful concentrations. Refer to the work Bruce Littman and I developed almost a decade ago to stress the first principles of translatability. Furthermore, because sufficient therapeutic disruption is taking place with respect to the virus creating havoc in the host response, additional factors may come into play. You have the option to mathematically model, given current data, whether your drug can elicit an effect clinically. Such models help with decision-making, simulating what-if scenarios that help calibrate expectations such that the assumptions behind that exercise is transparent. Remember, models are only as good as the data it’s built on and the assumptions. Better-informed experiments lead to models yielding realistic outputs.

Littman B and Krishna R. Translational medicine and drug discovery. Cambridge University Press, 2011 (URL: https://www.cambridge.org/us/academic/subjects/life-sciences/biotechnology/translational-medicine-and-drug-discovery?format=HB).  

4. Do I have the safety and exposure margins to test the concept in humans safely?
If you have an asset already in clinical development, then you might have identified a dose and regimen that is generally safe and well tolerated to evaluate in clinical trials in COVID-19 patients. On the other hand, if you have a preclinical asset, pay attention to the currently understood symptomology of COVID-19 patients and determine whether your compound needs unique considerations from that perspective. For example, if you have a compound that shows cardiovascular toxicity in animals, you may need to increase monitoring as one of the co-morbidities of COVID-19 is heart disease. You would also benefit from gaining alignment of your testing plans with the FDA or applicable local health authority.

5. How do I pick a dose and dosing regimen?
Once you have an IC50 against SARS-CoV-2 isolates, you could leverage simple modeling tools like physiologically-based pharmacokinetic (PBPK) modeling to pick the dose and regimen for use in a clinical trial. They assist with determining the pharmacokinetic exposure coverage with various dosing “what if” scenarios. More sophisticated models including drug-disease models (refer to the work of Kamal and coworkers) would leverage other features of the drug, including potential safety features that might otherwise limit full exploration of dose range in humans. Together, they help you visualize the therapeutic window, laid out in mathematical way but easy enough to interpret the outputs. You can also get prediction intervals that can help you determine the precision with which an expected effect could be attained. Patrick Smith and coworkers authored an excellent commentary recently that helps visualize the importance of dose and schedule in the context of COVID-19.

Smith PF Dodds M, Bentley D, Yeo K, Rayner C. Dosing will be a key success factor in repurposing antivirals for COVID-19. Br J Clin Pharmacol. 2020 Apr 17. doi: 10.1111/bcp.14314. [Epub ahead of print]

Kamal MA, Gieschke R, Lemenuel‐Diot A, Beauchemin CA, Smith PF, Rayner CR. A drug‐disease model describing the effect of oseltamivir neuraminidase inhibition on influenza virus progression. Antimicrob Agents Chemother. 2015; 59(9): 5388‐ 5395.

6. How do I pick the patient population that will have the highest probability of success?
The myriad spectrum of symptomology and comorbidities associated with COVID-19 complicates picking the right population for your drug. They also present an opportunity if you make the choice based on the best science and biological plausibility. Currently, the sensitive populations predisposed to COVID-19 include the elderly, anyone with underlying cardiovascular or respiratory disease, diabetes, renal disease, and immunocompromised persons (refer to CDC guidelines and look for updates to these guidelines as they provide an emerging knowledge base that will help your research). Your drug could work in patients with mild disease, moderate disease, and/or severe disease based on biological plausibility. Picking the right population will help you understand the biology and the potential of incremental innovation. You may also want to consider factors that could enrich your trial design. This bodes well with the maxim “learn and confirm.” We are in the learning phase with this design, and are all in it together.

7. What comparator should I use?
Your drug’s ultimate goal is regulatory success. From that perspective, you must design your trial so it presents an acceptable body of safety and efficacy evidence. Because there is currently no standard of care for COVID-19, the most prudent design is a randomized, placebo-controlled trial. There are, however, many presumptive standard of care options that are emerging, most notably remdesivir. Mining through clinicaltrials.gov website would give a glimpse into the types of clinical trials that are currently enrolling or in progress. There are many precedents to consider, most notably influenza and the emergence of Tamiflu as a standard of care. Certara scientists have been front and center in the development of Tamiflu and the work by Kamal et al provides that important framework.

Kamal MA, Smith PF, Chaiyakunapruk N, Wu DBC, Pratoomsoot C, Lee KC, Yi Chong H, Nelson RE, Nieforth K, Dall G, Toovey S, Kong DCM, Kamauu A, Kirkpatrick CM, Rayner CR. Interdisciplinary pharmacometrics linking oseltamivir pharmacology, influenza epidemiology and health economics to inform antiviral use in pandemics. Br J Clin Pharmacol 2017; 83:1580–1594.

8. What endpoints should I consider?
There are many endpoints to consider, including mortality, time to mortality, hospitalization, time to hospital discharge, symptoms, etc. These are detailed in FDA and other local health authority guidelines. Consider including all exploratory biomarkers and genomic signatures relevant to your drug’s mechanism of action. These will help you present the full story to the regulators, even though their effects may be unknown. Real-world evidence affords an accelerated pathway to registration, based on compelling weight of evidence.

FDA Guidance for Industry. COVID-19: Developing Drugs and Biological Products for Treatment or Prevention: https://www.fda.gov/media/137926/download.

9. How do I differentiate my product from the competition?
Many decision analytic tools are available that could help you evaluate how your drug stands out from the pack. You could also leverage model-based meta-analysis to mine randomized clinical trial databases and review competitive symptom scores or other clinical endpoints. These decision analytic tools help you make decision choices under uncertainty, leading to better quality decisions. Refer to the blog by Bill Poland and myself.

Krishna R, Poland B. Applying decision analysis to drug development for COVID-19 & future pandemics, 2020. URL: https://www.certara.com/2020/04/30/applying-decision-analysis-to-drug-development-for-covid-19-future-pandemics/?ap=IDD&UTM_LeadSource=

10. How do I ensure the operational success of my clinical trials from a regulatory perspective?
Many regulatory guidance documents have been rapidly released to facilitate an understanding of what regulators are looking for as you operationalize your clinical trial. The FDA has a webpage devoted to COVID-19 resources but also trial level guidance on design and execution of clinical trials (https://www.fda.gov/media/137926/download).

https://www.fda.gov/emergency-preparedness-and-response/counterterrorism-and-emerging-threats/coronavirus-disease-2019-covid-19


Rajesh Krishna, PhD

Rajesh has more than 20 years of drug development experience with past leadership roles in product value enhancement and quantitative clinical pharmacology at Merck, Aventis, and Bristol-Myers Squibb.  He holds an adjunct assistant professorship in therapeutics at Thomas Jefferson University.


What can Certara do for you?

We are drug development consulting experts offering a wide range of resources to facilitate the most streamlined, accelerated development pathway for your candidate assets in COVID-19 patients.
Contact us for further assistance. To take advantage of in silico workbench applications for hydroxychloroquine, lopinavir/ritonavir, chloroquine and azithromycin, check out the COVID-19 Pharmacology Resource Center.

About the author

By: Rajesh Krishna