{"id":42247,"date":"2022-10-31T05:00:00","date_gmt":"2022-10-31T09:00:00","guid":{"rendered":"https:\/\/blogs.sw.siemens.com\/simcenter\/?p=42247"},"modified":"2026-03-26T06:27:45","modified_gmt":"2026-03-26T10:27:45","slug":"personalized-precision-medicine","status":"publish","type":"post","link":"https:\/\/blogs.sw.siemens.com\/simcenter\/personalized-precision-medicine\/","title":{"rendered":"Personalized Precision Medicine"},"content":{"rendered":"\n
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We are all unique. Our nucleotide pairs, beliefs, memories, and life experiences are singular and inimitable. Most people I know take comfort in the idea that the mold broke after making them. Our oneness should be very material in administrating healthcare and tending to our medical needs. Unfortunately, it seems all that uniqueness has been broadly disregarded for decades. A few basic traits categorize us, such as gender and age, which have significantly influenced how diagnostics, devices, medication, and health sciences have evolved.<\/p>\n\n\n\n

Most medical treatments are designed for the average patient, for the average person, in other words, taking the “one size fits all” kind of approach. We’ve been doing this in medicine for decades, really centuries, for medical devices as well as drugs. The result is that some products might be successful in some patients, but for other patients, not so much, and for the third set of patients, those medical devices and drugs could be flat-out dangerous.<\/p>Mike Drues, president of Vascular Sciences. Taken from Personalized Healthcare\u2014Mike on Medtech<\/a><\/cite><\/blockquote>\n\n\n

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Each one of us is unique. So why has medicine focused on a “one size fits all” approach?<\/figcaption><\/figure><\/div>\n\n\n

The diagnostic procedure or remedy with the highest efficacy for the average patient becomes a defacto “gold standard” without taking into account more precise data. One size fits all means critical indicators derived from our personal needs are ignored.<\/p>\n\n\n\n

The one size fits all approach works… for a car<\/h2>\n\n\n\n

The one size fits all approach mimics the relationship between a mechanic and a car. Let’s classify visits to your local garage into three categories: regularly scheduled maintenance, repair work due to an accident, or a known\/unknown issue affecting the car’s performance. In each instance, the mechanic would follow a standard procedure to check, replace or troubleshoot the problem.<\/p>\n\n\n

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Is visiting your doctor just like taking your car to the mechanic?<\/figcaption><\/figure><\/div>\n\n\n

This approach ensures consistency. Repeating the most efficient and cost-effective steps for the same issue delivers the desired result with minimal chances of error, provided you have a good and honest mechanic. And this makes sense because you wouldn’t tell each Toyota Camry it is unique compared to all the other Toyota Camrys out there.<\/p>\n\n\n\n

Humans are admittedly much more complex than cars. We collectively share many similar traits. However, our uniqueness influences our healthcare and medical needs depending on the procedure or diagnosis. How does impersonalized medicine fail us?<\/p>\n\n\n\n

Treatment efficacy rate is not as high as you think<\/h2>\n\n\n\n

If you had to guess, how often are the medications and treatments received effective? More than 50%? 80%? It is hard to find a consensus on this metric. Realistically, without delving into the specifics of each treatment, it would be hard to produce a single number to represent a global average. That hasn’t stopped others from trying. There are wildly disputed figures, putting average effectiveness as low as 30%.<\/p>\n\n\n\n

The number needed to treat (NNT) \u2026 is the number of patients who need to be treated for one patient to benefit. For example, consider a drug that decreases mortality of a certain disease from 10% to 5%, an absolute risk reduction of 5% (1 in 20). That means that of 100 patients, 90 would live even without treatment, and thus would not benefit from the drug. Also, 5 of the 100 patients will die even though they take the drug and thus also do not benefit. Only 5 of the 100 patients (1 in 20) benefit from taking the drug; thus, 20 need to be treated for 1 to benefit, and the NNT is 20<\/p>Taken from Drug Efficacy and Safety – Clinical Pharmacology – Merck Manuals Professional Edition<\/a><\/cite><\/blockquote>\n\n\n\n

Let’s use the NNT data for an ischemic stroke treatment as an example, taken from Tissue Plasminogen Activator (tPA) For Acute Ischemic Stroke<\/a>. The effectiveness is time-dependant:<\/p>\n\n\n\n

Time to administer drug<\/th>NNT<\/th><\/tr><\/thead>
0 to 3 hours from onset<\/td>10<\/td><\/tr>
3 to 4.5 hours from onset<\/td>19<\/td><\/tr>
4.5 to 6 hours from onset<\/td>50<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Delayed treatment is critical in diminishing the effectiveness, yet even when administered in a timely fashion, only 10% of patients benefitted from the treatment. 90% were ineffective. There is a staggering savings of costly drugs and human resources to be had if a better approach could be employed.<\/p>\n\n\n\n

Diagnosis errors occur frequently<\/h2>\n\n\n\n

It is likely that most of us will experience at least one diagnostic error in our lifetimes, sometimes with devastating consequences.<\/p>Improving Diagnosis in Health Care<\/em><\/a><\/cite><\/blockquote>\n\n\n

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The costs of medical diagnostic errors. Taken from The Administration and Congress Agree: Reducing Harm from Diagnostic Error is an Urgent Patient Safety Priority – Society to Improve Diagnosis in Medicine<\/figcaption><\/figure><\/div>\n\n\n

The wrong diagnosis prolongs the suffering and illness of the patient and lowers the chance of a complete recovery. The phrase “time is muscle” was introduced by Eugene Braunwald, meaning the more extended a heart-related issue goes untreated, the more damage endured. There are irreversible and often fatal consequences when precious time is lost in an emergency.<\/p>\n\n\n\n

While many factors contribute to diagnostic errors, the question is, by using the average patient approach, are we increasing that probability? Is there critical information that a precision medicine approach includes which would change the diagnosis? The short answer is yes; more personalized data decreases the chances of misdiagnosis. Literature on this topic tends to focus on data management; existing patient records which are not easily sharable due to legislative or logistical barriers.<\/p>\n\n\n\n

Let’s look beyond a specific patient’s immediate needs and take a more systematic view, focusing on diagnostic procedures. It is possible to create a digital twin of the patient for use in CAE-type simulations for diagnosis. However, it is not commonly employed, even if the technology is ripe for exploitation. Simulation is no doubt an essential asset to the personalized precision medicine approach.<\/p>\n\n\n\n

Under the virtual knife <\/h2>\n\n\n\n
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