The pharma-free future- what if we stopped developing drugs?
Perverse incentives for the high cost of our life and death
Photo by Matthias Langwieser
A pharma free, physician-free future
This is part 1 of a 2 part series imagining a pharma and physician-free future.
This week, I dive into the perverse incentives for the high costs of pharmaceuticals. Next week, we’ll talk about a physician-free future with AI.
It’s all about the money.
Why did drug R&D costs grow 5X faster than the cost of living (or dying)?
Between 2008 and 2019, clinical trial costs doubled. The U.S. Consumer Price Index (CPI) rose 18.8%.
Why did this happen?
Even the AMA is unsure what’s going on. How much we spend on drug R&D is ‘nebulous’ (as a Jan 2025 article in JAMA that surveyed clinical trial costs called it. (the link to the article is at the end of this essay).
I’ll start with a personal story
5 years ago
I was in a course of physiotherapy after a cycling crash. My physiotherapist said at our last session, “You’re good to go now, but I noticed that you have hand tremor. You should see a neurologist”. I replied, “Yeah, I noticed that. I have double-clicks while typing”.
Nicole said, “See a specialist”.
I made an appointment with Prof. Nir Giladi, chief of neurology and movement disorders at Tel Aviv Medical Center. He had treated my mother for MSA and I had his phone number.
Nir performed a thorough workup and told me that I have a mild case of essential tremor. He said that neuroscientists have no idea what causes ET.
He wrote a prescription for me:
Do at least 5 hours of exercise/week
Don’t take medication
Don’t see doctors
Today, I exercise 9 hours/week - Qigong an hour/day and another 3 hours of cardio (walking and cycling). The double clicks are gone and the ET is mitigated. No drugs. No doctors.
What would happen if we took Prof. Giladi’s advice: Exercise, don’t take medication and don’t see doctors?
But first - show me the money.
The perverse incentives and cost structures of pharma
The CRO outsourcing model and high US hospital prices result in higher total CRO profits via higher costs to companies developing innovative therapeutics.
These costs are passed down to consumers after FDA clearance.
I take a look at the cost dynamics of clinical trials and the clinical trial value chain.
I’ll then consider an alternative business model that has the potential to change the way life science companies 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
By 2000, the US spent more on healthcare than any other country, whether measured per capita or a percentage of GDP.
It’s the prices stupid
U.S. per capita health spending was $4,631 in 2000, an increase of 6.3 percent over 1999. 4 The U.S. level was 44 percent higher than Switzerland’s, the country with the next-highest expenditure per capita; 83 percent higher than neighboring Canada; and 134 percent higher than the OECD median of $1,983. 5
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.
CROs have no incentives to go fast and reduce costs
CROS (clinical research organizations) are outsourcing organizations that provide an array of services for clinical trial management and monitoring, reporting and regulatory submission.
A CRO employs 2 basic outsourcing models, people sourcing and functional sourcing. In people out-sourcing, the drug company is responsible for managing contractors. In functional outsourcing, the company may buy a set of functions, for example study monitoring and medical writing.
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 pharma may elect to do it himself which shifts the CRO cost to an internal headcount cost, with internal overheads and technology costs.
There is no free lunch.
The result is a perverse incentive for delay and higher costs to bring innovative therapeutics to market.
The drug development outsourcing model and higher hospital prices drive higher total profits via higher costs to customers.
The higher cost of innovative treatments is then passed down to consumers (patients) after FDA clearance.
A comparison to other industries: Microsoft, Apple, AWS, Netflix, AirBnB, Uber
Consumer value chains
A consumer value chain looks generically like this:
Suppliers -> Distributors -> Consumers
By the early 90’s, the PC industry led by Intel and Microsoft used a 2-tier value chain:
Microsoft->Distis->Resellers->Customers
Resellers were further segmented according to 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->Distributors->Resellers->Consumers
By the mid-2000s, Amazon AWS (including Netflix and the entire cloud service / SaaS industry) evolved the channel model to 0-tiers with a direct 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
The common thread is that AWS and Netflix deliver a digital product end-to-end, whereas Airbnb and Uber aggregate trusted suppliers inside the Airbnb and Uber brand environment and provide an outstanding and uniform user experience to all the consumers.
This is in contrast to the patchwork user experience a customer got from the 90’s Microsoft channel. There are great resellers and terrible resellers.
We will return to user experience and aggregation later.
The clinical trial value chain
The first published RCT (randomized clinical trial) in medicine appeared in the 1948 paper entitled "Streptomycin treatment of pulmonary tuberculosis". One of the authors of that paper was Austin Bradford Hill, who is credited as having conceived the modern RCT.
The drug development value chain looks strange when we see how Intel, Microsoft, Amazon and Netflix evolved their own value chains.
There are typically 3 tiers with patients that are both suppliers and consumers.
Patients->Hospitals->CROS->Life science 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->Life science companies->Patients
The dystopian user experience in drug development
The user experience is at the core of Apple’s and AWS success stories. Outstanding user-experience and aggregation are the hallmarks of companies like Airbnb, Netflix and Uber.
In drug development, little has changed in the past 77 years since the Streptomycin trial.
Granted – the SARS-COV-2 pandemic accelerated change 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 2025) of clinical trials and hospital operations still have a mixed bag of complex expensive, difficult-to-use IT with a value chain that creates a dystopian user experience for hospitals, patients and medical device companies.
Multiple, pasted-together systems in a mish-mash of proprietary and off-the-shelf video technologies has little to do with healthier people.
HCOs (healthcare operators) rely on data collection technology procured by companies running clinical research (sponsors and CROs). This creates a number of inefficiencies:
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.
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 is logistically difficult due to the number of EDC vendors on the market (over 50 established companies).
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.
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 clinical trial model is loss of focus on the patient user experience.
Upstream and to the left, patients are subjects of a trial. Not consumers of a product.
Downstream and to the right (what FDA calls ‘post-marketing’), patients are consumers.
After drugs clear to market, the patient experience and data change.
The patient UX in real-life is totally different than the UX in a clinical trial.
The data in real-life is disconnected from the clinical data in studies.
Potential future models - Vertical integration and aggregation
We previously claimed that hospital site costs are high for clinical trials.
How high are they relative to consumer healthcare?
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 non-interventional 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 clinical trial done on the Flask Data platform, the sponsor paid sites $700K: 10X the cost of a premium consumer healthcare plan. (There were no medical imaging and blood test requirements).
Perhaps the law of small numbers is killing us here. The way to solve that is with aggregation and vertical integration.
Let’s return to the clinical trial value chain.
As we can see, there are many moving parts and a disconnect between the patients in the clinical studies and healthcare consumers in the real world.
Healthcare consumers->Hospitals->CROS->Life Science companies->Patients
Integrate backwards and to the left
One alternative is to integrate backwards and to the left. This requires managing hospital site functions and to a certain degree is done in the SMO (site management organization model).
Integrate forward and to the right
The other alternative is to integrate forward and to the right. This is the path that Airbnb, Uber and Netflix took aggregating consumer demand with an outstanding user experience. The aggregation gives Airbnb, Uber and Netflix buying power to the left, enabling them to choose the best and most cost-effective suppliers.
The value chain would then look like this:
Suppliers->Life Science companies->Patients
This is a model that we see increasingly with medical device companies.
The medical 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 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
The reality is that using a technology platform with vertical integration is more expensive initially for the drug company. It should be.
Under-funding your infrastructure results in time delays and cost spikes to the pharma company at the end of the study.
The current CRO methodology of study close-out at the end of a clinical trial lowers costs during the trial but creates an expensive catch-up process at the end of the study.
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.
The rule of thumb is that it costs 100X more to fix a defect after the product is manufactured than during the manufacturing process.
This is true for clinical trials as well.
A real-time alert on protocol non-compliance during the study can be resolved in 5 minutes. At the end of the study, it takes hours or days of work-flow, data clarifications and emails.
What if we stopped developing drugs?
We can reduce costs of drug development by engineering better supply chains.
But there are far more cost-effective and life-effective alternatives.
The best way to reduce costs is not to develop the product
Can you imagine an Ozempic-free world?
What if we stopped developing drugs?
What if we never visit doctors?
Next week, we take it even further — What if AI replaces doctors entirely?
• Drop a comment—what would it take for YOU to never need a drug again?"
• "Hit reply—how would you redesign healthcare if prevention was the goal?"
❤️ To my readers, my love and gratitude for reading my work. If you’re not a subscriber, now would be a great time to support my work.
I want to invite you to my new podcast - “Life Sciences Today”.
If this piece got you thinking, you’ll love my new podcast. In my first episode, I dive into AI’s role in accelerating clinical development with Orr Inbar from Quanthealth.
Once a week, I host people changing the life science industry in drug development, clinical operations and real-world data.
👉If you’d like to be a guest on the show - let’s talk!
👉 If you enjoy reading this post, feel free to share it with friends! Or feel free to click the ❤️ button on this post so more people can discover my writing. 🙏
For a recent discussion of clinical trial costs see this January 2025 JAMA article:
“Use of Clinical Trial Characteristics to Estimate Costs of New Drug Development”