Several very senior pharma executives were recently overhead by a journalist discussing what each of them viewed as the most important changes in the way healthcare will be delivered over the coming decade.  Each of them listed several such factors, including increased payor pressure on prices, the mounting regulatory burden and the shift toward orphan indications, but there was unanimity on just one factor: the importance of personalized medicine.

Personalized medicine is the great white hope for the pharmaceutical industry: by only treating the fraction of the population who can benefit from a particular medicine, efficacy and value-for-money are substantially increased.  But the prices set by Pfizer and Abbott for lung cancer drug Xalkori™ (a dual c-met and ALK kinase inhibitor) and its companion diagnostic (a FISH assay for translocations affecting the ALK genes) following its US approval last week, while on the face of it being unremarkable, nevertheless raise questions about the personalized medicine business model.

Xalkori™ crizotinib will cost $9,600 per month, yielding $50k to $75k per patient for the full treatment regimen – expensive, but pretty much in line with other newly approved medicines for small patient groups (only about 5% of non-small cell lung carcinomas – those with transloactions affecting the ALK gene cluster – are amenable to treatment with this drug).

The Vysis ALK Break Apart™ FISH probe test, from Abbott, which identifies the patient subset sensitive to treatment with Xalkori™, by contrast, will cost less than $250 per patient.  Again, this is entirely consistent with pricing structure of DNA-based diagnostics used in the clinic.

So if there is nothing surprising about these prices, what’s the problem?  The distribution of income between the drug developer and the diagnostic developer is heavily biased towards the drug.  It’s not as extreme as the unit prices for the products suggest, because the diagnostic should be applied to a wider population to identify the target population.  So with 100 non-small cell lung carcinoma patients tested with diagnostic (raising $25,000 revenue for Abbott), 5 will be identified who are suitable for treatment with Xalkori™ (raising $375,000 revenue for Pfizer), assuming full penetration of the market in both cases.  The diagnostic product, therefore, garners about 6% of total spend on the test and drug combined.

There are lots of obvious reasons why this is the case: the cost of developing the drug product was more than 10-times higher than the development costs for a typical diagnostic.  Drugs take longer to develop, and have a much higher risk of failure.  The regulatory hurdles are much higher for drugs than diagnostics.  And in any case, the need for the diagnostic only became clear because of the success of the drug.  In short, 6% of the overall returns for the diagnostic partner in such a situation sounds generous.

However, the situation in oncology, where the vast majority of companion diagnostic products currently on the market are located, hides a bigger issue: the difficulty in earning rewards for genuine innovation in the field of diagnostics.  In oncology, not a great deal of innovation is required on the companion diagnostic side, since the test is tightly tied to the mechanism of action of the associated therapeutic.  In such situations, there is virtually no technical risk associated with the development of the diagnostic product.  The only risk is regulatory risk (which is relatively easy to mitigate, at least for the big players who well understand the process) as well as risk that the associated therapeutic fails to win regulatory or market acceptance – in which case sales of the diagnostic product will also be non-existent.

But in other indications, finding companion diagnostics will require much more innovation.  For example, in chronic inflammatory diseases picking people who might show the best responses to anti-TNFs requires something more innovative than tests for genetic variation in the TNF-a gene or its receptors.  Because the biology of inflammation is complex, predicting the responses to drugs (even those with well defined molecular mechanisms) is a substantial challenge – a challenge that, for the most part, remains unmet.

Indeed, in some cases innovations in biomarker discovery might actually drive new therapeutic approaches:  the management team of Total Scientific, in collaboration with Imperial College, London, discovered that low circulating levels of the amino acid proline is a powerful new biomarker for osteoporosis, predicting fracture risk as well as low bone mineral density.  This finding not only suggests that a diagnostic assay for serum proline may be clinically useful, but that therapeutic strategies directed to modulating proline metabolism may also be effective.  Our innovation in biomarker discovery may ultimately open up a whole new field of bone biology, spawning multiple high value therapeutic products.

In these situations where innovation is required in both the diagnostic and therapeutic domains (which will probably prove to be the majority of personalized medicine product combinations), a business model that splits the revenues 94% to the drug developer and 6% to the diagnostic developer seems skewed.  If the driving innovative step came from the biomarker end (as in the example with proline), the team with the original insight may hope to reap at least half the reward.

There are two major reasons why this is unlikely to happen: firstly, there is a glass ceiling on price for a diagnostic product.  Paying more than $200 or so for a molecular diagnostic, no matter how innovative or complex, is contrary to almost every healthcare reimbursement system worldwide.  Secondly, the barriers to prevent competition against the therapeutic component of the product combination are very high indeed (both from regulatory and intellectual property perspectives).  But in marked contrast, the barriers to prevent another competing product being launched against the diagnostic assay component of the combination are very much lower.

These two factors will likely combine to restrict the return to innovators in the diagnostics space relative to those in the therapeutic space, irrespective of the apparent value of their innovation.

This state of affairs is bad for everyone.  It limits the incentive for real investment in biomarker discovery independent of therapeutic development, so the chances of finding innovative new companion diagnostics outside of oncology are materially reduced.  As a result, even though (for example) a new test to determine which RA patients might respond best to anti-TNFs would be beneficial to patients (avoiding exposing patients to the drug who will not benefit and immediately giving them the opportunity to try something else without waiting 6 months to see of they responded), and also beneficial to payors by reducing the number of patients treated with an expensive drug.  Indeed, the economics of such a test might sustain a price for the product that was well above $200.

Yet the second problem would then intervene to drop the price: competition.  Since it is (usually) impossible to protect the concept of measuring a particular analyte (and is only possible to protect a particular methodological approach to its measurement), others would most likely be free to develop different assays for the same analytes.  As the regulatory hurdles for developing competing tests is low – particularly once the first test has been launched, since fast-followers need only demonstrate equivalence – it would not be long before the first product to successfully predict responses to anti-TNFs among RA patients would be subjected to competition, driving prices back down again.

Subtle though they seem, the differences in the IP and regulatory landscape for diagnostic tests compared with therapeutics, threaten the viability of the personalized medicine business model.  Delivering on the promise of personalized medicine for both patients and the healthcare industry requires allocation of capital to drive innovation in both biomarker discovery and identification of novel therapeutic targets.

At first sight, developing diagnostic products, as opposed to therapeutics is relatively attractive.  The limited demand on capital, short time-line to product launch, low technical and regulatory risk and the substantial medical need all favour developing diagnostic products.  But not if the discovery component becomes lengthy and expensive.  In other words, developing “me-better” diagnostics makes a lot of commercial sense, but investing in genuine innovation in biomarkers still looks unattractive.  And it is precisely these highly innovative new diagnostic products that will underpin the delivery of personalized medicine.

What can be done?  Not a great deal in the short term, perhaps.  But in the longer term, much needed reforms of the regulation of diagnostic products might raise the barrier to competition against first-in-class assay products.  The current regulatory framework for therapeutics is draconian, demanding very high levels of safety from every aspect of the drug product, from manufacturing to long-term side-effects.  By contrast, despite some tinkering in recent years, the diagnostic regulatory framework remains relatively lax.  Home-brew tests are introduced with little regulation of manufacturing standards, and the focus of the regulators is on the accuracy of the measurement rather than on the clinical utility of the result.  This leaves open a weak-spot in the overall protection of the patient, since an inaccurate diagnosis (leading to incorrect treatment) can be as harmful for the patient as treatment with an inherently unsafe medicine.  Just because molecular diagnostics are non-invasive, it doesn’t mean their potential to harm the patient is zero.

There are moves to close this loophole, and the unintended consequence of such regulatory tightening will be an increased barrier to competition.  Perhaps the addition of a period of data-exclusivity, much as applies in the therapeutics world, could be added in addition to further protect truly innovative diagnostic products from early competition.

Such moves are essential to make innovation in biomarkers as commercially attractive as innovation in therapeutics.  It will be difficult to achieve in practice, however, as pressure on healthcare costs ratchets up still further over the coming decade.  Competition, lowering prices, is on the surface attractive to everyone.  But it is the differing protection from competition between therapeutics and diagnostics that leads to skewed incentives to invest in innovation in one area rather than the other.  Lets hope that once combinations of therapeutics and companion diagnostics start to appear outside of oncology, the relative pricing of the associated products properly reflects the innovation in each of them.  If it doesn’t, our arrival in the world of truly personalized medicine may be delayed indefinitely.

Dr. David Grainger
CBO, Total Scientific