The spread of COVID-19 has presented one of the greatest challenges of recent times, and the impact will be felt on a personal, economic, and global scale for decades to come.
As there are currently no effective therapies to prevent or treat COVID-19, the scientific community is racing to identify safe and effective vaccines and medicines to prevent and treat the disease. Progress is being made at a phenomenal rate and scientists around the world report collaboration between typically competing companies like we’ve never seen before.However, whilst the progress is truly impressive, the medical and scientific community has a responsibility to ensure the evidence to support both efficacy and the safety of these treatments is based on robust data. To quote Sherlock Holmes: “It is a capital mistake to theorise before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.”
This twisting of facts is evident in the hype over chloroquine/hydroxychloroquine as a ‘miracle cure’. Initial studies were small, uncontrolled and uninterpretable, but generated undue publicity and indeed hope. A multinational registry review has now concluded there is no benefit but potential harm associated with chloroquines1.
We know from experience that response to medicines is not evenly distributed across those exposed to them and is influenced by both intrinsic and extrinsic factors. If we fail to provide sufficient evidence to support the benefit-risk of treatments and vaccinations, then we expose global populations to three potential risks:
- providing ineffective medicines to large populations;
- providing effective medicines that also cause significant harm when given to large populations; or
- in the worst scenario of all, providing ineffective medicines that also cause significant harm to populations.
As we race towards development of new treatments and repurposing of existing ones, we must also draw on previous experience and previous unexpected outcomes to identify possible issues with novel therapies early on. For example, the lessons we have learned from Dengvaxia are very instructive to vaccine development. Dengue fever is a widespread and serious disorder that is prevalent in Asia-Pacific. Individuals who were given Dengvaxia but who had not been previously exposed to dengue virus suffered an increased risk of severe dengue with subsequent virus exposure. This resulted from something called ‘antibody-dependent enhancement’ in which the body’s immune response actually makes the clinical symptoms worse and increases a person’s risk of developing severe disease. Based on experience with the development of SARS vaccine2, this is a definite concern for COVID-19 so it will be essential to determine whether individuals have been previously exposed to the coronavirus as part of benefit-risk assessments as the vaccine is rolled out.
Antivirals such as Gilead’s remdesivir look compelling, as the science supports the mechanism of action and evidence from preclinical studies suggests it may be effective in related coronaviruses (MERS and SARS) so there is a higher probability it will be successful in COVID-19. Likewise, immunosuppressants such as Roche’s Actemra (tocilizumab) could interrupt the process of ‘cytokine release syndrome’ (CRS), a form of serious inflammatory response that can occur as a complication of COVID-19 infection. Indeed, therapeutic remdesivir treatment initiated early during infection has a clear clinical benefit in SARS-CoV-2-infected rhesus macaques3. The latest preliminary data from a study being run at Chicago University Hospital indicates that patients experienced rapid recoveries from fever and respiratory symptoms. While encouraging, until the full trial data has been released and analysed, these results must be viewed as speculative.
Nevertheless, coming back to the suggestion of ‘miracle cures’ like the antimalarial drug chloroquine/ hydroxychloroquine, we must be wary. Anecdotally researchers believe it may have some beneficial effects either through antiviral or immunosuppressant effect in COVID-19 subjects, but the mechanism of action is not fully understood. However, although the efficacy of the drugs as a COVID-19 treatment might be uncertain, their side effects are not. They include ventricular arrythmias resulting from prolongation of QT interval. “What I know for sure as a cardiologist is that these powerful medications have important side effects including rarely sudden cardiac death,” said Michael Ackerman, a genetic cardiologist and director of Mayo Clinic’s Windland Smith Rice Genetic Heart Rhythm Clinic4.
In order to facilitate appropriate clinical decision-making, it is absolutely essential that the pharma community builds a body of scientific evidence to support the use of medicines or vaccines across large numbers of people and against the characteristics of the individual through robust and reliable studies. The pressure to evaluate potential therapeutic options and vaccines means that formal trials will be attenuated, and therefore approval will almost certainly include a variety of risk management commitments: ie Emergency Use Authorisation by the US Food and Drug Administration or Enhanced Safety Surveillance by the European Medicines Agency.
This means we will see significant effort directed to gathering data in the post-approval setting whether through Large Simple Trials or spontaneous data capture. One of the key requirements for diseases such as COVID-19 is to include background diseases within data sets as many patients will have pre-existing conditions such as hypertension and diabetes. It will be essential to understand whether individuals with those conditions or on particular medicines have a different risk profile when they are exposed to COVID-19 compared to people who are not, ie do their medications help or hinder treatment?
Taking vaccination as an example, until manufacturing capability has been scaled up it is likely that vaccines will initially be rolled out to the highest priority populations in the first instance. Namely healthcare workers, the elderly and those who have been identified as vulnerable. This means that vaccines will relatively quickly move from a relatively small, healthy population to a large, heterogenous population with a wide range of pre-existing conditions. Therefore, it will be essential to obtain safety data quickly and run signal detection against relevant background. It is essential that we understand the impact these factors have on the efficacy of a COVID-19 vaccine and the potential risk not just in the broad population, but also stratified by subgroups.
We need sufficient data across populations with these chronic conditions to understand the variation in risk profile of both COVID-19 itself, and whether any associated treatments alter response to the infection or to treatments. It is only through systematic capture of large, standardised data sets that we will build the body of evidence required to make informed clinical decisions on the appropriate medicines to prevent and treat the different stages of COVID-19 across a diverse population.
To quote Professor Shibo Jiang who warns in a recent Nature article: 'Testing vaccines and medicines without taking the time to fully understand safety risks could bring unwarranted setbacks during the current pandemic, and into the future.'5 It is our duty to ensure that regulators, healthcare providers and patients are provided with medicines that are supported by robust data sets that build the body of evidence required to make informed clinical decisions on the appropriate medicines to prevent and treat the different stages of COVID-19.