Why medtech companies should ask wrong questions

Every question is a cry to understand the world. There is no such thing as a dumb question.   Carl Sagan

In this guest post, my colleague Tigran Arzumanov asks questions about questions.  Tigran is an experienced and highly talented business developer for life science companies and he’s been around the block a few times.

What to do when a medical device company  asks the wrong questions?

I am sure we’ve all been there.

You meet the senior management of an innovative medtech company. They’re looking for a contract manufacturing partner or a regulatory consultant or an embedded software developer or a clinical research platform. You know you can deliver.  You’ve done dozens of projects like that.

They’re concerned about quality and on-time delivery.     You want to qualify them and make sure they are a good fit for your offering.

You came in on time, you are prepared. You know you can deliver to the client needs. The greeting is welcoming, genuine and heartfelt, the handshakes are firm. Smiles all around. You sit down and start talking. And, little by little, you start finding out what the client wants.

As you hear more and more, your sunny cheerful mood starts dripping away, little by little.

You realize that that the medtech company’s picture of the project and the conclusions that he’s made are drastically different from yours. That the client is likely to reject what you offer, because they want something you do not sell.

Yet, you’ve seen this a dozen times already and you know what the client wants to do won’t work.

What to do

There’s no point in trying to argue your point. Win an argument – lose a client – I learned that this quote by Peter Drucker is as true today as it was in the 80s.

In some cases, you will have to walk away and hope the medical device company realizes soon enough that they are on the wrong track – and once they do, they will remember who gave them a truthful answer.

Whether you close the prospect on that first meeting, or after a year of  conversation, the key is to get to no.   

Getting to no is a great starting point for you to understand the client needs.   Getting to no is also a great way for the client to understand that there are advanced technologies out there that can help him bring his connected medical device to market faster.

A former colleague had a favorite saying – ‘a good vendor answers a client’s question well, a great vendor tells a client what questions they should be asking”.

Carl Sagan was a physicist.  Physicists are curious people by nature. This saying is a great way to make the client curious.

In my experience, most people will ask ‘so, what questions do you think I should be asking?’ Then you are not pushing your vision and ideas, but keep on answering the questions. The client is still in control. And if this phrase has not triggered their curiosity, perhaps you are better off walking.

Another way to mildly give a version different from the one the client asks is to give an anecdote from your experience. Acknowledge what the client has said, and then say “actually, I had a client in a similar situation”. If the flow of the conversation allows it, make a pause so that the client asks how it turned out – and then deliver the story. Few people will resist the temptation to listen to a story about someone in a similar situation to them – and if they pass, perhaps you had no business being in a meeting with them in the first place.

Tigran Arzumanov is an experienced business development/sales consultant running BD as a service, a Contract Sales Organization for Healthcare IT and Clinical development.

 

 

 

 

 

 

 

 

 

Curious about how cloud technologies and AI can help you get your medtech product faster to market?

100X faster to deviation detection in medical device studies.

Automated Patient compliance deviation detection and response on the flaskdata.io platform for a connected medical device clinical trial is 100X faster than manual monitoring. Automated compliance monitoring analytics and real-time alerts let you focus your site monitoring visits on work with the PI and site coordinators to take total ownership and have the right training and tools to meet their patient recruitment and patient compliance goals.

Strong patient adherence in real life starts with strong people management

Hagit.jpg

Patient adherence in real-life starts in clinical trials determining the safety, side effects and efficacy of the intervention, whether a drug or a medical device.

Like any other industry – success in clinical trials is all about the people.

The hugely successful movie – “Hidden figures” tells the story of the gifted black women mathematicians who played key roles in the NASA space program in the Mercury and Apollo space programs. It is a moving, inspiring and (sometimes hilarious) story of how NASA, a dominantly white male organization came to accept diversity during American desegregation.

By comparison, the Israeli life science industry lives in a different time and place and women are in leadership roles at all levels  of Israeli life science companies.

In this 4 part series of articles, we will tell the story of the gifted Israeli women who are the   “Hidden figures” of the Israel biomed/biotech industry.

Women comprise about 65 percent of Israel’s biotechnology workforce, and about 13 percent of top management positions in companies listed on the Tel Aviv Biomed index. In order to find out what attracts Israeli women into this globally male dominated field, I talked to a number of well-respected women, tried to learn about their story, get acquainted with their mindsets and solve the “mystery” of Israeli women invading this field.

Part 1 of the series tells the story of Hagit Nof – former Country Manager of IQVia in Israel and  currently the COO & BD of nRollmed an Israeli startup that helps clinical trial sponsors speed up their study using online patient recruitment and optimization.

(IQVia is the world’s largest provider of biopharmaceutical development and commercial outsourcing services ).

Hagit has a great story of a dream come true for a person who was not afraid to make a risky decision at the right time and was able to build a career in the biopharmaceutical industry literally from scratch.

(more…)

Why you do not want to unify data in your medical device clinical trial

Unification of data from patient medical records, hospital reports and clinical trial protocols is a tempting yet extremely dangerous idea.

In this outstanding guest post, security and privacy expert, Veronika Valdova from Arete-Zoe explains why merging medical records, hospital reports, and clinical trial data is a very bad idea.

 Data breaches endanger your clinical trial success

Medical privacy and breaches of personal health information (PHI) has been a hot topic for several years. For the clinical trial industry, the main concerns are decline in recruitment resulting from lack of confidence in data handling and instances of breaches that affect data integrity that adversely affect NDA and MA applications in major markets, which precipitates administrative action taken by national regulators in response to local incidents.

(more…)

You can DIY a chair from IKEA. You cannot DIY your medical device clinical trial

By: Jenya Konikov-Rozenman

I think the word ‘DIY’-Do It Yourself is one of the most popular words that I hear lately and although I can’t put my finger on it, DIY stars in almost every field imaginable. It starts with planning our vacation on-line without going out to meet a travel agent, knitting warm scarves for the coming winter instead of buying one, decorating an event hall for a party by arranging thousands of flowers in amazing combinations that can be found on-line and furnishing our apartment with furniture that we carried from IKEA and of course built ourselves using their guide and all of it without professional help!

Don’t get me wrong, I have nothing against DIY; I admire people that can do things by themselves and I hope one day I will DIY stuff instead of buying ready-made things from the mall or calling for a decorator to arrange flowers for my special event.

But my question is, can anything be DIY? Or is DIY and online self-service just one more trend that will die out and we will go back to old traditions of using professionals?

I am a PhD candidate in Biology. As scientists, we believe in the principle of doing thing ourselves and constantly challenging ourselves with new experiments. We also believe in reaching out to the right people for advice and assistance. When we buy ready-made reagents, antibodies and solutions, it’s for only one reason: allow us keep focused on what we need to do, our research! This is my motto and I believe in it. Unfortunately, we can’t do everything by ourselves, but if we find the right people with the best solutions for our needs, we can reach our goals easier, better and faster.

Medical device clinical trials are experiments, designed to test and prove or disprove a scientific hypothesis and determine the clinical endpoint.

According to the NCI definition – “the clinical endpoint is main result that is measured at the end of a study to see if a given treatment worked (e.g., the number of deaths or the difference in survival between the treatment group and the control group). The clinical endpoint is decided before the study begins.”

We can readily see that in order to calculate the clinical endpoint, we need to collect data accurately and in such a way that the data can be easily reduced and analyzed.

Translated into more specialized terms from the world of computer science, we say that we need to start with a good data model, collect data, validate it and populate the data model with the data we collected. Then – we can calculate the clinical endpoints.

And this is why I am skeptical about giving sponsors of medical device clinical trials self-service tools for building an EDC (Electronic Data Capture) application. As a matter of fact, it can be a very bad idea as witnessed by the hair-raising story of the medical device vendor who performed a self-service study without collecting the primary endpoint.

Brilliant in biotech and clueless in computer science?
For some time now, I’ve been working with several brilliant Israeli R&D companies that have taken amazing ideas from concept to real products. They had an idea, they found investors, recruited money, forged partnerships, and hired the right people for R&D, manufacturing and QA/QC. They enlisted medical doctors, biologists, bio-statisticians and many more specialists and invested days on end, writing the precise study protocol and the best CRF.

All that hard work was done for one reason: to find better ways for diagnosis, cure and, treatment for people like you and me.

But, if there is one thing that I keep seeing over and over again (and to be honest, it’s a little scary) is that great scientific innovators are not so great when it comes to building an EDC for their medical device clinical trial. They can be brilliant innovators of non-invasive monitoring technology and forget to collect the primary endpoint. They can design an innovative slow-release drug and design an EDC that misses contraindications and under/over-dosing.
Which would be a disaster.

Confusing IT ease-of-use with clinical trial success?
Google the search term “self-service EDC clinical trials” and you will get 113,000 hits on companies that supply DIY EDC solutions for medical device clinical trials. These companies will offer you a Web-based DIY package, ready-made templates and allow you fit them to your paper CRF. You write some general validation logic and basically you’re good to go on with your clinical trial. Sounds great, easy and cost effective but let me tell you a little secret, the EDC game is not rosy and cheerful.

Without a doubt, self-service cloud EDC offerings for medical device clinical trials are hot and seductive. In the famous last words of an esthetics device sponsor we know – “what’s the big deal? It’s just a few tables in a Business Objects database”. Last time, I checked, she was still stuck in that sentence…

Let’s consider some examples of clinical trial failure due to inappropriate design and edit check implementation.

Edit checks – a curse instead of a blessing?
Poorly-designed ECRFs and edit checks can drive your sites crazy during the trial. Edit checks can be as simple as validating an age range or as complex as correlating age, gender, informed consent, medical history and baseline screening.

Medical device trials can have anywhere from 200 to over 800 edit checks relating to dozens of ECRFS on a timeline of 25 patient visits and more.

These edit checks are the equivalent of the London underground or the New York City subway system. The objective of these complex, highly interrelated systems is to get you from point A to point B but if you make the wrong connections, you miss your train, your station and find yourself in a crummy neighborhood you never wanted to see.

Correct design and execution of edit checks will allow early detection of data quality issues and reduce the amount of time your study monitor spends on source data review.

And what about changes?
You may not have anticipated that the FDA wants you to collect additional data or change inclusion criteria in the middle of the study. After you write a letter to file, you will have to change the EDC – but if your self-service Web app doesn’t support versioning (and some don’t) you are stuck with a stack of old data over here and new data over there. Go figure out how to analyze here and there. You may have to trash your old data, create a new version of the EDC and re-enter all the data.

And what about the statistical analysis?
At the end of the study, you will work hard to clean the data, only to discover that your data model is intractable making it difficult to extract the data in a useful structure for statistical analysis and only then you discover that your results are statistically insignificant and that all that extremely hard work went down the drain.
A robust data model will allow you to perform the statistical analysis without expensive rework by the study statistician.

Show me the money!
For example, let’s take a multi-center medical device clinical trial that expected to last for 24 months with 500 subjects. Assume cost per subject of USD 10K for recruiting, lab tests, PI costs etc. and add another 20% for onsite monitoring and you get USD 6M for the study cost. A cloud EDC service will cost around USD 1000/month. The trade-off is DIY study build versus hiring a qualified professional to build the study. Internal costs of employees for DIY build and QA would be a minimum of 3 man-months, say USD 30K assuming an FTE costs USD10K/month. A professional study build might cost USD 60K; taking the DIY alternative saves you USD 30K on a study that costs USD 6M; or a savings of 0.5 percent at the risk of endangering the success of your entire trial.

The risk of failure is not always justified by cost savings.
DIY EDC is an IT productivity tool that may be a good fit for small investigator-initiated studies, but for multi-center trials, the risk is not justified by the cost savings.

So please tell me why risk the success of your trial and reputation for the pleasure of DIY?
DIY your vacation, but have a specialist design and implement your study data collection, validation and monitoring.

Jenya Konikov-Rozenman is a PhD candidate in biology and a project manager at FlaskData.io.   She can be reached at the FlaskData.io contact page.