Perverse incentives for the high costs of drugs and delayed access to patients

The long and lonely road for a CRA

This is an essay I started writing over a year ago.

I just discovered it in my folder of drafts.

Today — one might claim that the essay is no longer relevant. After all — look how Pfizer and Moderna ramped up RNA technology into a vaccine in less than 12 months.

Then again — look how AstraZeneca, one of the great life science companies didn’t make it to the finish line and mis-dosed 20% of their patients in their pivotal clinical trial.

Perverse incentives for price tags

More importantly, the outsourcing model does not link directly to business success.

You may discover after a year that you need to trash your R&D investment. Surely this is not a price that your CRO pays.

In this essay, we’ll take a look at the cost dynamics of clinical trials and the clinical trial value chain.

We’ll then consider an alternative business model that has the potential to changes the way drug and device sponsors conduct clinical trials, reduce costs, shorten time to FDA submission and reduce risk of failure and last-minute surprises.

The high costs of US hospitals

It’s the prices stupid

It’s the prices, stupid.

In 2011, the US Affordable Care Act set a requirement for MLR (Medical Loss Ratio) that insurers must spend 80–85% of revenue on medical services. This reduced insurer margins, and drove up hospital prices to make up for lower margin.

The CRO business model

Neither CRO model has an explicit incentive to complete a study faster since that would reduce outsourcing revenue for the CRO. The more time a CRO spends on monitoring, site visits, SDV and study closeout, the more revenue it generates.

A drug or device sponsor may elect to do it himself which shifts the CRO cost to an internal headcount cost supplemented with additional costs for consultants with risk and time delays by not having the CRO expertise and infrastructure.

TANSTAAFL

The result is a perverse incentive for delay and higher costs to bring innovative therapeutics to market.

The CRO outsourcing model and higher hospital prices drive higher total profits via higher costs to customers. The higher cost of innovative medical devices is then passed down to consumers (patients) after FDA clearance.

Consumer value chains

Suppliers -> Distributers -> Consumers

By the early 90’s, the PC industry led by Intel and Microsoft used a 2-tier value chain:

MSFT->Distis->Resellers->Customers.

Resellers were further segmented according the customer size and industry segment — Retail, Large accounts, SMB and VARS (value-added-resellers) selling their own products and services to a particular industry vertical. The PC industry value-chain model left Microsoft with 50% of the SRP (suggested retail price) and delivered products to customers that were 45–50% less than SRP, leaving the channel with 0–5%.

The channel was forced to implement extremely efficient operations and systems and sell value-added services and products in order to survive.

By the new millennium, Apple introduced a 1-tier model with a user-experience designed and controlled by Apple.

The Apple 1-tier channel looks like this:

Apple->Apple Stores->Consumers

Eventually the Apple channel model broadened to include a 2-tier model similar to PC industry:

Apple->Distis->Retail->Consumers

By the mid-2000s, Amazon AWS (and generally the entire cloud service / SaaS industry) evolved the channel model to 0-tiers with a direct-to-consumer subscription and delivery model.

AWS->Consumers

As AWS grew and introduced spot pricing, an aggregation sub-market developed, looking extremely similar to movie and TV distribution models.

AWS->Aggregators->Consumers

AWS also became a distribution channel for other cloud products similar to content distribution (Think Netflix).

Third-party products->AWS->Consumers

Outstanding user-experience and aggregation are the hallmarks of companies like Airbnb, Netflix and Uber.

We will return to user experience and aggregation later.

The clinical trial value chain

The clinical trial industry value chain looks strange after understanding how Intel, Microsoft, Amazon and Netflix evolved PC, cloud and streaming industry value chains.

The clinical trial value chain typically has 3 tiers with patients that are both suppliers and consumers.

Patients->Hospitals->CROS->Medical device companies->Patients

In a SMO (site maintenance organization) model, we have 2 tiers which improves things a bit, however as we will see — the SMO model does not necessarily improve the economics, risk management and user experience.

Patients->SMO->Drug and device companies->Patients

The dystopian user experience of clinical trials

Granted — the SARS-COV-2 pandemic is accelerating change at a tremendous rate with more and more use of shiny-new decentralized trials and direct-to-patient platforms.

Despite the upsides of decentralized clinical trials in a pandemic world, the vast majority (> 90% as of Jan 2021) of clinical trials and hospital operations still have a plethora of complex expensive, difficult-to-use IT with a value chain that provides a dystopian user experience for hospitals, patients and drug and device companies.

Decentralized trials introduces new challenges.

We believe that the problem of multiple, pasted-together systems has only been exacerbated with the rapid introduction of online patient interactions using a plethora of proprietary and off-the-shelf video technologies.

HCOs (healthcare operators) rely on data collection technology procured by companies running clinical research (sponsors and CROs). This creates a number of inefficiencies:

1. HCO staff are faced with a variety of systems on a study by study basis. This results in a large amount of time spent learning new systems, staff frustration and increased mistakes. This is passed on in costs and time to sponsors after CRO markup.

2. The industry is trending towards the use of eSource and EMR to EDC data transfer. eSource/ePRO tools need to be integrated into the patient care process. Integration of EMR with EDC becomes logistically difficult due to the number of EDC vendors on the market (over 50 established companies) and complexity of current EMR systems like Epic.

3. Siloed data collection in hospitals with subsequent manual data re-entry results in large monitoring budgets for Source Data Verification, and delays caused by data entry errors and related query resolution. Delays can be on the order of weeks and months.

4. Use of multiple disconnected clinical systems in the hospital creates a threat surface of vendor risk, interface vulnerabilities and regulatory exposure.

Losing focus on patients

One of the consequences of the 4-tier medical device clinical trial model is loss of focus on the patient user experience.

Upstream and to the left, patients are ‘subjects’ of the trial.

Downstream and to the right, patients are ‘consumers’ of trial outcomes.

The patient reported outcomes apps they use vary from study to study. Downstream and to the right (what FDA calls ‘post-marketing’), patients are consumers of the medical device or drug. The real-world user experience is totally different than the UX in the study. The real-world data of drug efficacy and safety is disconnected from the clinical trial data of drug efficacy and safety.

Clinical trial validation

Who owns patient compliance to the research protocol in the supply chain? The medical device sponsor, the CRO, the hospital site or the subject?

The CRO may not collect a patient compliance metric since he outsources to the hospital. The hospital may not have the tools and the medical device company is outside the loop. My essay on determining when patient compliance is important in medical device trials goes into more detail on the problem of losing focus on the patient.

Vertical integration and aggregation

In 2016, Medicare Advantage primary care spend was $83 PMPM (per member per month). Let’s say that a premium service should cost $100 PMPM. Let’s use that as a benchmark for the cost of processing a patient in a medical device trial. Take a Phase II medical device trial with 100 patients, running for 10 months:

That’s 100 x 7 x 100 = $70K for patients.

In a medical device trial recently done on the Flaskdata.io platform, the sponsor paid the hospital investigatory sites $700K — 10X the cost of a premium consumer healthcare plan. (There were no medical imaging and blood test requirements).

Killed by small numbers?

Healthcare consumers->Hospitals->CROS->Life science companies>Patients

Integrate backwards and to the left

Integrate forward and to the right

The value chain would then look like this:

Suppliers->Drug and device companies->Patients

This is a model that we see increasingly with Israeli medical device vendors with limited budgets. The drug or device company uses a cloud platform to collect digital feeds from investigators, patients and devices and automate monitoring for deviations. Focus on the patient user experience begins with design of the therapeutic and continues to post-marketing and real-world.

Aggregation of patients enables purchasing power with suppliers — research sites, clinical consultants and study monitors.

Short-term versus long-term cost allocation

It should be.

Under-funding your infrastructure results in time delays and cost spikes to the life science sponsor at the end of the study.

Pay me now or pay me later

The catch-up process of identifying and closing discrepancies can take 2–6 months depending on the size and number of sites.

The catch-up process is expensive, delaying submission to FDA and revenue since you have to deal with messy datasets.

However, the true cost of catch-up is the risk of failure. Consider AstraZeneca.

This is true for clinical trials as well. A real-time alert on treatment non-compliance during the study can be resolved in 5 minutes. By waiting to the end of study it will take a day of work-flow, data clarifications and emails to the PI.

You may discover after a year that you need to trash your R&D investment. Surely this is not a price that your CRO pays.

Summary

I am a physicist by training, serious amateur musician and everyday biker. Working in cybersecurity and AI-driven monitoring of clinical trials.

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