Monkeypox vaccine: a case study for real-world data

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OWith health emergencies becoming more common, the world needs better ways to test drugs for safety and effectiveness, even if they haven’t yet completed the long series of clinical trials that the Food and Drug Administration usually requires. Data on the actual use of new drugs offers an increasingly valuable and effective means of doing this.

This is how the authorities were able to determine that the first vaccines against Covid-19 were safe and effective on a large scale in 2020. Because the virus was spreading so quickly, it only took a few months to start seeing the difference in outcomes between trial participants who received an actual vaccine and those who received a placebo. Later, in 2021, when data showed significant numbers of vaccinated people were infected, health experts quickly instituted advice for additional booster shots.

And now, in a welcome development that could have ramifications for future drug approval methods – and could even lead to more affordable drug prices – real-world data is positioned to play a vital role in assessing effectiveness of monkeypox vaccines.

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After last summer severe shortage of monkeypox vaccines, the FDA has approved an emergency alternate dosing schedule for the Jynneos monkeypox vaccine. This allows health officials to administer the vaccine intradermally, with each dose being only one-fifth of the original approved dose. The idea is to ensure that as many people as possible are vaccinated.

Although such an approach, in which the vaccine is injected only into the outer layers of the skin rather than into the muscles or other deeper tissues, has not been tried with this vaccine or similar vaccines on a large scale. , it exists research indicating it might work – and a for other types of vaccines – because the skin contains many cells that defend the immune system.

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With limited vaccine doses and no ability at any time in the past to test dosage changes, or even the clinical effectiveness of the vaccine against actual exposure to monkeypox in humans, the only way to establish the efficiency now, at least in the short term, will be to collect and analyze real-world data. In fact, the efficacy of the initial dose against actual monkeypox infection was tested only on animals while its safety and levels of antibodies produced in the bloodstream are tested on humans, meaning scientists have little knowledge about how it works, how long it lasts, whether it stops transmission and other factors.

While the spread of monkeypox has slowed, the United States still sees around 200 new cases a day and has been home to a third of all cases worldwide. It is in this context that the researchers of the Centers for Disease Control and Prevention and elsewhere are taking the opportunity to track the data to see how well the Jynneos vaccine works at its lowest dose under real-world disease exposure. The National Institutes of Health, in cooperation with the FDA, will also collect and study data on intradermal injections to determine their effectiveness. Faced with the real risk of infection as the virus continues to spread, being able to see whether those vaccinated are also infected or not will show how well the vaccine works (or doesn’t work) in its new dosage form.

Real-world data (and real-world evidence) can also play a role outside of public health emergencies like Covid and monkeypox. They can help determine the long-term effectiveness of many treatments, especially those subject to the fast-track approval process, such as those used for rare diseases, and can help determine the value of drugs in general. In many cases, clinical trials are not enough to understand the true effectiveness of drugs. Janet Woodcock, director of the FDA’s Center for Drug Evaluation and Research, said the clinical trial system is “broken” and that greater use of real-world evidence could be an effective complement to the approval process.

The FDA has taken steps to use more real-world data outside of public health emergencies like Covid and monkeypox. In 2018, the agency issued directives for the use of this evidence in drug approval. In 2021, when the FDA released improved guidance on the subject, real-world evidence had been used in approve 90 medical devices and the new drug use, Prograf. But this does not happen enough in practice.

Failing to use real-world data means missing out not only on a better understanding of the effectiveness of each drug, but also on a chance to improve the entire pharmaceutical sector, in particular by tackling problems such as rising costs. The availability of more data on the actual outcomes of the use of medicines, particularly gene therapies and other innovative and often very expensive treatments, would pave the way for pricing that takes patient outcomes into account through approaches such as value-based contractwhen health insurers base drug prices on how well drugs work in the people taking them, rather than just pre-market clinical trials.

Former FDA Commissioner Scott Gottlieb said that the ideal approach would be a hybrid system that uses both clinical trials and real-world evidence, with real-world evidence serving as a means to further validate clinical trials, which are often limited to small numbers of people and only include those participants likely to respond positively to therapy.

Drugs will still have to go through supervised levels of laboratory testing and clinical trials. But real-world data can and should play a bigger role. Although modifying the dose of the monkeypox vaccine due to a shortage is not ideal, if officials use this opportunity to collect and study data on its effectiveness in the midst of an ongoing epidemic, they can show the role important that these data can play in the evaluation of drug efficacy. Real-world data and evidence, when used in the right way, can help better determine the effectiveness and value of a drug or vaccine, ensuring a more efficient approval process. This, in turn, could lead to a better and more equitable healthcare system.

Girisha Fernando is the Founder and CEO of Lyfegen, a Swiss-based company focused on software analytics for value-based contracts in healthcare.

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