You’re a biopharmaceutical innovator. The FDA approved your new therapy for patients with a specific type of cancer. How do you commercialize your new drug? More importantly, how do you reach the patients who can benefit from your therapy and ensure it’s being used and prescribed in the right way?

The answer to both questions is data and analytics. Data and analytics can drive your commercialization and clinical plans at each step of a cancer patient’s journey—from access to use to outcomes.

Let me explain why your biopharma company needs a data and analytics strategy now more than ever. I’ll then discuss how to build that strategy and use the insights from it to improve results for your business and for your cancer patients.

Simplify the complexity of the oncology drug market

The market for oncology drugs is becoming more complex. Patients don’t just have cancer. They have a specific type of cancer with specific tumor characteristics, biomarkers, and mutations that are unique to them because of genetics and other medical conditions.

As cancer diagnoses become more precise, your therapies are getting more complex as you try to target individual cancer patients with those specific genetic and medical conditions. And complex therapies usually mean complex treatment regimens.

That clinical complexity hasn’t stifled competition. As you know, the fastest-growing therapeutic area of new drug launches is oncology. You and other biopharma companies are in a crowded field that gets more crowded by the day.

Complex cancer drugs are costly. That means reimbursement is getting more complex. In a value-based care world, efficacy is critical. Health plans and pharmacy benefit managers (PBMs) want to assess available evidence and the trade-offs between cost and value before considering how to include your drug in their formularies.

But there’s a light at the end of the tunnel. A data and analytics strategy can simplify things so your biopharma company can respond to these demands in the right way.

Three building blocks of an effective data and analytics strategy

The right data and analytics strategy will give you a 360-degree view of a patient’s journey on your new oncology therapy.

You need three blocks to build that comprehensive view. The three building blocks are:

1. Data. The first thing you’ll need is a variety of data. This just isn’t about volume of data, but ensuring that you are getting the full range of the right data to meet all of your stakeholders’ needs. You need data from each point in your patient’s treatment journey, and it's a very complex ecosystem. The types of clinical and financial data you’ll need to collect include: patient access; genetic, molecular and other diagnostic test results; medical history; medication history, use and adherence; social determinants of health; demographic indicators; claims and reimbursement; medication and treatment regimen; clinical outcomes; patient-reported outcomes; real-world evidence; and supportive care.

2. Platform. All of this data comes from disparate sources, such as electronic medical records (EMRs), claims and reimbursement systems, lab reports, pharmacy management systems, inventory management systems, disease registries, clinical trials, published medical research, in-home health evaluations, mobile health devices, patient portals, social media channels and more. Most of this data is structured, and some of it is unstructured. So the second thing you’ll need is a platform that can ingest all the different types of data from these sources. It’s a daunting task for a biopharmaceutical manufacturer. But this is the only way your biopharma company can create a holistic view of each patient who can benefit from your new oncology therapy.

3. Experts. The third thing you’ll need is people. These are the experts who can look at the data you’ve collected on your platform from the disparate sources and make sense of it all. They can advise you on what actions you should take based on what the data says. The experts include: analysts; biostatisticians; economists; epidemiologists; clinical specialists; data scientists; oncology nurses; pharmacists; and oncologists.

These people can bring it all together and see what’s truly happening during the continuum of care for patients you’ve targeted with your new therapy.

Laying the groundwork for a successful cancer treatment program

So what sort of things can the data tell you, and what action do you need to take? The best place to start is at the beginning: patients.

The data can identify patients who could benefit most from your new oncology drug. The data will tell you what type of cancer they have, what biomarkers they have, and what other medical conditions they have that could make them candidates for your new drug. Knowing and identifying your potential market is essential to commercialization.

Next up are physicians at oncology practices who could potentially prescribe your new drug. The data will inform you of their practice profile, prescribing patterns, treatment preferences and willingness to try your new drug to treat their cancer patients. You can use those insights to craft awareness and education campaigns to help physicians make the best clinical decisions for their patients.

Payers are players in this scenario, and data can help you with health plans and PBMs, too. The data will help you understand health plan coverage and reimbursement trends, so you can develop targeted market access strategies. You can also ensure that your patient support programs are being leveraged to help manage the patients’ costs.

Use data to drive optimum outcomes for your oncology therapy

You’ve identified the right patients for your oncology drug. You’ve educated physicians on the right way to prescribe your drug. And you’ve cleared the way for health plans and PBMs to cover your new drug. What comes next is the crucial part, and that’s whether your drug is working. And the data will tell you that too.

You can use the insights from your data and analytics strategy to:

  • Assess whether specialist prescribers are using your oncology therapy
  • Identify why and when prescribers are using your therapy
  • Reveal utilization patterns and prescribing practices
  • Document providers’ provision of supportive care and medications
  • Generate and capture the real-world outcomes of your therapy

You can use those insights to demonstrate the clinical effectiveness and value of your new oncology therapy to payers. And you can use those insights to support regulatory submissions to the FDA.

Most importantly, the insights from your data and analytics strategy allow you to take actions that lead to the best clinical outcomes for your patients—and the best business outcomes for your biopharma company.

Related: Learn more about McKesson’s data, evidence and insights solutions for biopharma companies

Derek Rago

About the author

Derek Rago is the VP and General Manager of Data, Evidence & Insights for McKesson Life Sciences. He is responsible for leading the commercial informatics, HEOR and clinical education solutions for oncology. Derek has more than 20 years of experience in business management and strategy with the last 14 years focused on the healthcare sector. He holds an M.B.A. with a dual emphasis in Marketing and Finance from Arizona State University and a Bachelor of Commerce from the University of Alberta, Canada.

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