Logo RGB Strap Line

inTrigue Business Case

Volv has spent three years developing its flagship product called inTrigue, which finds misdiagnosed and undiagnosed rare disease patients from electronic health care records (EHRs). inTrigue is based on an entirely original use of artificial intelligence and machine learning, together with a set of established in-country processes that access tens of millions of EHRs.

In a recent project, inTrigue was deployed for a biotech that had just received market authorisation for a rare metabolic disorder in eight countries, with a combined population of 428 million. Prior to the Volv project, the predicted number of affected (but undiagnosed) individuals in this population was believed to be 541, based on established prevalence figures. No incidence figures were known by the company, and it therefore had no estimate of growth of in treatable population. The inTrigue product determined a different prevalence, predicting 2,121 undiagnosed affected individuals, and it was also able to determine the incidence.

Executive Summary

Volv can demonstrate with evidence that its method of determining prevalence is more accurate than all other current approaches. Current estimates of prevalence are typically based on extrapolations from previously found (and correctly coded) patients, which for rare and ultrarare diseases is inherently difficult given how few patients there are in any patient population.

Current approaches, by definition, will not have found the ‘hidden’ patients, who have been diagnosed inaccurately or clinically ignored, for example, and at best these approaches code current clinical thinking only. Current approaches miss entirely the insights possible from blending deep learning on the whole gamut of published medical thinking across a multiple-million, anonymised patient population, which is the inTrigue approach to determining prevalance.

This paper models the financial impact of finding and treating these additional patients on both the biotech’s revenue and its sales and marketing costs, by adopting the inTrigue deployment methodology.

Revenue Growth

Pharmaceutical company revenue derives from patient case finding and prescribing

Patient cases may be found from:

  1. Research databases of EHRs
  2. Health records, from either primary care or hospital settings
  3. Clinician diagnosis by primary care and specialist physicians

The table of potential revenues below models the impact of deploying the Volv InTrigue methodology onto the example biotech’s newly identified patient population. This newly identified population is additional to the known patients that may already be coded in the EHRs. The following assumptions are applied to reduce the population to avoid over-claiming the potential impact.

  1. We down-rate the number of patients that can be found. For a given EHR dataset we estimate that only 75% of the patients may be findable (due to the noisy nature of the data)
  2. For the healthcare system itself we estimate that red flagging may catch a further 35% of the existing population, as it depends on clinician uptake amongst other things.
  3. We estimate that even with a positive diagnosis, the conversion to prescription is 75%

Additionally, we have assumed a pricing model of cost per patient per year; other pricing models, e.g. cohort pricing, value pricing, etc. and the impact of market entry arrangements can alter the top line growth and improve the value proposition to payers.

The inTrigue process takes between 12 months and 18 months to complete for each country, with the elapsed time varying according to time required to comply with the particular country data regulations. Completion is defined as having found and had diagnosed the target patients existing in the country databases available, and the red-flagging system set up.

This will give a realistic time to initial revenue of 18 months to two years from project inception, with revenue maturity expected within three to four years of project inception.

In Trigue Bus Case Chart Grey L

Significant new revenue potential

Cost Reduction

The Volv inTrigue methodology delivers two outcomes that have a direct bearing on sales and marketing costs: it provides an elegant way of educating and gaining the support of key specialist KOLs (in the rare disease); and it provides at the primary care level an automated way of identifying undiagnosed patients and getting them to KOLs.

Given the traditional role of an in-country team is to educate KOLs and interact with often hundreds of primary care providers, these two outcomes deliver a much lower requirement for sales and marketing personnel.

Based on discussions with existing pharma clients, we would estimate a reduction in personnel of at least 30% and possibly 50% is achievable. In practice, Volv assigns its value engineer consultants to work with its pharma clients to determine potential savings in staffing and other marketing costs.

Summary

The inTrigue methodology blends original data science with a set of robust delivery processes to find undiagnosed and misdiagnosed rare disease patients. Rare disease pharmaceutical companies that choose to adopt inTrigue – as distinct from taking either a traditional approach or a conventional AI search approach – can expect to achieve an increase in addressable market size, combined with a significant reduction in cost of patient acquisition.

Find out how we can help you build a business case with inTrigue