Target Product Profiles: A Strategic Framework for Healthcare Startups

Many healthcare startups are founded on deep technical or clinical expertise. But turning that into real-world impact—and a sustainable business—is another challenge altogether.

One of the most overlooked tools in this process is the Target Product Profile (TPP): a strategic blueprint that aligns innovation with market needs, regulatory requirements, and reimbursement pathways.

In this article, we’ll look at how founders can use TPPs to design better products, speed up their go-to-market plans, and boost clinical adoption.

Target Product Profile:
Starting point for Strategic Thinking of Healthcare Startups 

Kakao Ventures meets numerous prospective and early-stage entrepreneurs. In the healthcare sector, which I am in charge of, it is common for founders to have expertise in technology or medical services.

While expertise is a significant advantage for startups, it is neither a necessary nor sufficient condition for becoming a promising company. We’ve seen cases where excellent university hospital professors have yet to become promising entrepreneurs. 

So, what capabilities should one possess to become a good entrepreneur besides expertise? 

Although there are various factors, such as leadership and talent acquisition, I would like to highlight strategic thinking. There are diverse methodologies for strategy, but I would like to focus on Target Product Profile (TPP) as a starting point for healthcare startups. 

TPP means envisioning the product the company wants to develop as concretely as possible. For example, in drug development, it means to outline what will be included on the label when the drug candidate receives FDA approval. A drug’s TPP typically includes ▲indications ▲target patients ▲dosage ▲administration method ▲ contraindications ▲ side effects, etc. 

TPP is useful when applied to first-in-class type of items. Tech-based founders often focus solely on the technology itself without considering its business aspects. Especially in the healthcare business, where the lead time (from product planning to sales) is long, entrepreneurs often lose sight of their “business” purpose. By considering the business elements of the product through TPP early on, founders can focus on what really matters for their business to succeed.

Contents of TPP 

So, what is a TPP composed of? 

TPP generally includes the contents as shown in the table below. It is a method of organizing in writing, one by one, the factors that need to be considered for the product to smoothly go through processes such as FDA approval, insurance coverage, and field adoption.

When startups draft TPP, I advise them to focus on the U.S. market. That is because most domestic markets are not big enough and US is the single most important market. It means that most healthcare companies eventually need to go to the US. So, having a strategic plan in the US context is important. 

TPP Example of a startup 

Now, let’s write a brief TPP using Kakao Ventures’ portfolio company, ARPI, as an example. 

First, we need to understand what product ARPI is developing. ARPI makes an “ECG-based AI patient triage system.” This system assists emergency room physicians in decision-making. I will provide an example along with photos.

A patient with acute chest pain that started 3 hours ago visited the emergency room showed the following ECG. Based on the circumstances, myocardial infarction is suspected. However, the typical ST-segment changes are not visible, and deep T-wave inversions are observed in V1~V3. In this situation, myocardial infarction can be primarily suspected for the time being.

The following results are obtained when ARPI’s AI analyzes the ECG above.

The result shows that the likelihood of ACS (Acute Coronary Syndrome) or STEMI(ST elevation Myocardial infarction) is low. Instead, the probability of RV dysfunction (right ventricular abnormality) and PulmHTN (pulmonary hypertension) is very high. Combining acute chest pain and these results, this patient has a high likelihood of pulmonary embolism.

ER physician using ARPI can increase the accuracy of diagnosis. However, medical AI often receives questions about its value, such as “Can the patient outcome improve just by diagnosing a little more accurately?” 

ARPI can answer that question as follows. In emergencies, every second counts. Much more than other settings such as outpatient departments. So, medical AI intelligence like ARPI, which helps doctors make faster and more accurate decisions, is sufficiently valuable. 

Based on this description of ARPI’s AI, let’s at the table above on the contents of TPP to write one for ARPI.

(1) Indication

AI analyzing ECG can be used for various purposes. It can be used for all purposes except treatment, including ▲screening ▲risk stratification ▲ definitive diagnosis ▲ companion diagnosis ▲monitoring. Among these, for which purpose is it most likely to receive insurance reimbursement? 
(Insurance reimbursement is not the only business model for medical AI. However, since it is the most critical business model, let’s create a TPP based on insurance reimbursement model.)

In the case of ARPI, the indication of “risk stratification” in the emergency room seems most plausible. The reason why other indications don’t work well is explained below.

• Screening (finding abnormalities in the general population before symptom develops) is hard to prove value.

• Confirmatory diagnosis is challenging to gain superiority over more expensive and accurate existing tests (e.g., coronary angiography, pulmonary artery CT).

• Companion diagnostic is closely associated with specific diseases with expensive drugs, but it is difficult for ARPI to find such an association yet.

• Monitoring is often the case for arrhythmias such as atrial fibrillation rather than general emergency conditions. 

Considering these factors, the most appropriate purpose for ARPI seems to be “(emergency room) risk stratification”. It guides ER physicians through diagnosis/treatment decisions for patients. It does not necessarily be limited to the emergency room and has a chance to develop its scope into other hospital settings.

(2) Target Patients 

ARPI’s target patients are “patients with moderate or higher severity visiting the emergency room”. This is because electrocardiograms are often not performed for mild or lower-severity ER patients. There is no need to distinguish between genders. The age group is likely to be 50–60 years old or older, as they are more likely to visit the emergency room for cardiovascular diseases.

(3) Target Payer 

The most relevant payer in the United States is Medicare. This is because the majority of patients visiting the emergency room for cardiovascular diseases are 65 years old or older.

(4) Existing Clinical Workflow and Changes After ARPI adoption

The existing clinical workflow at ER with regards to ECG is as follows:

‘Patient arrives at the ER’ → ‘ECG is performed while blood tests are done’→ ‘ECG is instantly available while it takes time to have blood test results’ → ‘ER physician analyzes the ECG along with blood test results’ → ‘ER physician decides which tests to perform first (e.g., Echocardiography, Pulmonary CT angio, Cardiac Angiography, etc.) → ‘If the test comes out negative. try other tests until the physician comes to a diagnostic conclusion’

Within this workflow, there are often two issues. The first issue is that ECG is sometimes inconclusive, which means that physicians need to wait for the blood tests. The second issue is that even the blood tests are inconclusive. For example, level of Troponin-I, which is performed to diagnose Acute Myocardial Infarction, doesn’t change much in the early hours of disease onset. In this case, physicians need to repeat the test every 4 hours. In case of D-dimer test, which helps diagnose pulmonary embolism, its normal value rules out the diagnosis. But elevated value is often non-specific. The issues mean that additional help is warranted for the timely diagnosis of the ER patients. 

ARPI comes handy here. It helps physicians order more plausible test before others even without blood test results. As a result, time to diagnosis can be reduced. Since every second counts at ER, reducing diagnostic time helps improve patient outcomes.

When considering the clinical workflow, the impact of new technology on the overall work should be considered as well. If the current workflow has to change significantly with the introduction of the new product, physicians or hospitals may be reluctant to adopt it. 

What about the environment where ARPI will be implemented? In the emergency room where ARPI will be used, various tests, including ECG, are already being performed. ARPI, which is an AI-based algorithm, doesn’t require much work from ER personnel. Therefore, even if ARPI is implemented, there is a high possibility that physicians or hospitals will not need to change their existing workflow.

(5) Differentiation from Existing/Competing Technologies

There are other ECG AIs in the market. However, most of them deal with arrythmia. Others don’t address ER patient diagnostic issues comprehensively. So, ARPI seems to be competitive in this specific clinical setting. 

What about other blood tests done in the initial evaluation of ER patients, such as Troponin-I, BNP, D-diemr, etc. As mentioned earlier, ARPI doesn’t try to replace them. ARPI is more about complementing the blood test results. 

Considering the conservative nature of medicine, tests considered “standard” are not easily replaced. When you develop a new type of test, you need to either complement existing tests or target an environment where there are no similar products. However, in the case of second situation, physicians may not feel the strong need for the product. 

Working with TPP

So far, we have conceived TPP through the example of ARPI. 

It can be summarized as follows. “ARPI is an ECG-based artificial intelligence ER patient triage system targeting Medicare enrollees aged 65 and older. It aims to shorten the time required for emergency diagnosis and improve patient treatment outcomes by analyzing the ECG at the ER related to cardiovascular disease, helping the emergency room physician to determine which emergency disease is more likely. ”

The well worked-out TPP can be a guiding star for the startups. Startups may make strategic decisions based on TPP. Let’s assume how ARPI make decisions about the U.S. clinical trial.

First, the test subjects are Medicare enrollees aged 65 and older. The test site is the emergency room. Going one step further, would it be better to do it at a university hospital or a regional secondary hospital? The place where these patients mainly visit is more likely to be a regional secondary hospital rather than a university hospital. Then, conducting clinical trials at regional secondary hospitals as much as possible would be a good choice. In this way, we can include as many of our target patient groups as possible.

Many startups struggle with daily decisions without regard to their long term strategic goal. Drawing up the precise picture of their ultimate goal helps them visualize it and decide what to do now to achieve the goal.

At the same time, it is essential to review how much my decision helps us reach our goal. I hope this article will be helpful for startups’ strategic thinking.

Written by Chiweon Kim, a Vice President in the Investment Team at Kakao Ventures.