Volv Global Blog

Real World Evidence, Rare Diseases, Innovation, Regulation, Data Science, Predictive models, Patient Finding, inClude, Machine Learning

The Path to Rare Disease Clinical Trial Innovation

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Executive Summary

For decades, the pharmaceutical industry has faced the same recurring problems with clinical development: the struggle to fully recruit and retain enough patients, meet target timelines, and have trials conclude on time.

Certainly, the industry does overestimate its ability to recruit, but a bigger issue is that study designs and protocol development seemingly fail to truly reflect patients’ lives, or account for the reality in the clinic. In fact, data shows the probability of success for any clinical development effort is 6.2% for orphan drug trials, compared with 13.8% overall, which translates to a 93.8% failure rate for orphan drug development efforts.

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Volv Global SA and WODC EU contributors

Real World Evidence, Rare Diseases, Innovation, Data Science, Predictive models, Patient Finding, inTrigue, democratising the data, inClude

From Mendel to genetic rare disease diagnosis: Two centuries of innovation.

Credit Photo by John Towner on Unsplash

Enlightened breakthroughs...

More than 350 million people live with rare disorders, that is, a condition with which fewer than 200,000 have been diagnosed. About 80 percent of these rare disorders are genetic in origin, and 95 percent have no treatment approved by the FDA.

Our ability to better understand, diagnose and potentially find treatments for these conditions was significantly advanced by the Human Genome Project (HGP). From October 1990 until its completion in April 2003, the HGP brought together a team of international researchers who collectively defined over 90% of the human genome [i].

However, it would be fair to argue that the journey to understanding the human genome began with Gregor Johann Mendel, who is now recognised as the father of genetics. Born 200 years ago, in 1822, Mendel put his interest in plant genetics into practice with pea plant experiments conducted between 1856 and 1863, which established many of the rules of heredity, now referred to as the laws of Mendelian inheritance [ii].

His work was published in 1866 but was then forgotten about until 1900, when three researchers, Hugo de Vries, Carl Correns, and Erich Tschermak, independently realised the meaning and importance of Mendel`s groundbreaking work.

Mendel’s theories were finally associated with human disease by Sir Archibald Edward Garrod, who published the first findings from a study on recessive inheritance in human beings in 1902 [iii]. In 1909, the term “gene” was introduced for Mendel’s “traits” [iv].

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Léon van Wouwe

Real World Evidence, Rare Diseases, Innovation, Data Science, Patient Finding, inTrigue, democratising the data, inClude

2022 07 WODC USA Workshop - How can AI inform better Clinical Development strategy, design, and patient stratification?

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Rare disease drug developers face significant challenges during clinical development, from finding patients to conduct their trials to addressing heterogeneity in the target patient population. To help rare disease innovators establish a better clinical development strategy, Volv is co-conducting an in-depth Workshop at the World Orphan Drug Congress (WODC) Boston, USA, which is being held between the 11th to 13th July 2022. Come and meet us at Booth #318.

Join us at our Workshop on Monday 11th July 15:00 to discuss:

Putting AI to work for rare diseases: How can AI inform better Clinical Development strategy, design, and patient stratification?

The Workshop will consider AI’s potential with inClude, for revolutionising how companies operate in the rare disease space. Areas that will be explored include:

novel approaches to obtaining new insights,
uncovering new information from claims data,
ways to better define target patient populations and novel endpoints, and
gaining new insights into the disease earlier in its progression.

Download the Workshop Agenda here:

Christopher M de M Rudolf

Real World Evidence, Rare Diseases, Innovation, Data Science, Predictive models, Patient Finding, patient experience, democratising the data, inClude

It’s time to rethink clinical trial protocols, and ensure inclusive designs through democratising our health data, in a privacy-preserving way

Credit Photo by Marc Zimmer on Unsplash

It’s time to rethink...

Throughout my career in the pharmaceutical industry managing clinical trials and study programs, I have been confronted with the same recurring problems. Trials struggle to recruit and retain enough patients, they fail to meet target timelines and the vast majority don’t conclude on time.

There are some staggering statistics in the industry, for example, 86% of clinical trials don’t reach recruitment targets in the specified time and 90% of clinical drug development fails.

One obvious reason for these shocking figures is that the pharmaceutical industry overestimates its ability to recruit. But, more troublingly, study design and protocol development seemingly fail to truly reflect patients’ lives or account for the reality in the clinic.

Download the Blog here:

Léon van Wouwe