Developing Next Gen Multiple Sclerosis Therapies: Part 3
The following is part of a MStranslate exclusive series which highlights the struggles and obstacles in developing the next generation of therapies and drugs for human disease. Dr. Travis Stiles is a neuroscientist who has worked to develop regenerative therapies capable of reversing neuronal damage caused by disease and trauma, such as multiple sclerosis and spinal cord injury. Part one of this series can be read here, while part two is available here.
You can help support his efforts by clicking here. Every contribution helps move this work closer to these revolutionary discoveries becoming therapeutic realities.
Now that we have set the stage with the drug development process, we can begin to examine possible ways to adapt the system and improve outcomes. We know that the rate of new therapies and cures has slowed, so how can we right the ship and accelerate innovation? What are the unique obstacles and issues that hinder our progress today? How is this different than in the past?
Modern Innovation – The Scientific Method
Fundamentally, all innovation comes about in a very similar fashion. It starts with observation. Maybe it’s observation of a need, how things interact, or how the world behaves. For the curious, observation leads to conjecture. Why does this thing exist? How does it work? What is really taking place? These questions then evolve into hypotheses. The human brain is naturally discontent with observation alone, it wants to understand. So, we come up with our theories of why things are the way they are, a way to conceptualize and understand the world around us.
In most situations, the explanations we come up with to understand are often enough, no further work is needed as long as this new understanding makes sense in explaining the world around you. However, to advance understanding, we must go beyond what makes sense into what is testable and verifiable. This is where conceptualization becomes innovation, where theories become hypotheses that must be proven. To prove a hypothesis, it must be tested. Upon getting the results of our test we can begin drawing conclusions as to the accuracy of our hypothesis. Receiving this novel observation of this new piece of information we again return to additional questions for testing and the cycle goes on.
At its core, all invention stems from the application and repetition of this cycle over and over until a satisfactory product or idea is complete. However, the pace of this process can vary drastically from one field to the next.
Technology overall seems to be evolving at an ever-quickening speed. Consider that it was just over 10 years ago that the very first iPhone was released. In just 10 years we have gone from a device that was a serviceable telephone and music player to phones that can live stream broadcasts to millions of people, record super-slow motion high-definition video, and access the internet at speeds that put the fastest computers from 10 years ago to shame. When it comes to tech, innovation seems to be coming faster and faster. Yet for some reason, drug development has slowed. How can this be?
To some extent, this is because tech is able to build off itself in a way that medicine cannot. Each iPhone was an advancement on the previous, improving on core capabilities and incorporating additional innovations. While there may be some semblance of this with medicine, the reality is that drug development is not progressive in the same way. At its core, each newly discovered drug exists largely in a vacuum, and the efficacy of a drug cannot be increasingly improved upon over time the same way as tech. If a new component of a cell phone doesn’t work in the next model, the old version can still be used or other compensations made. For drugs, at a certain point, success or failure is binary and there is little room for product evolution.
This ability to iterate is a major reason why tech innovation has accelerated and medicine has not. When someone invents a new app, cell phone, engine, etc., these innovations can immediately be tested in the real world. Apps can be tinkered with, cell phones used to place calls, and engines driven. Feedback regarding the functionality and utility can occur almost instantly. Such rapid feedback facilitates real-time problem identification and modification, allowing for quick and efficient iteration. Such is not the case with medicine. Unfortunately, this only scratches the surface of the unique problems that limit the progress of drug discovery and development.
Innovation and Drug Development
Curing disease, and making new drugs, is arguably one of the most difficult forms of innovation. In comparison to tech and engineering, iteration is painfully slow and demonstrating efficacy can be extremely complicated. In general, medicine also doesn’t evolve in the same way other technologies can. In fact, even if we assume that a discovered drug is ideal for treatment of a disease, the application and evaluation of such technology is slow. While evaluation of the next iPhone can be carefully quantified and market tested, the human body is nuanced, complicated, and the observation of changes occurring within it might take several days, weeks, months, or even years. If you want to see how well a new drug treats cancer, not only do you have to administer the drug over a period of time, but you also have to wait for the cancer to spread, progress, shrink, remit, etc. Unfortunately, when it comes to human disease, we do not have the luxury of immediate performance observation.
Innovation, Drug Development, and the Brain
By no means am I intending to downplay the difficulty of drug development for tissues outside of the brain. Let me be clear, it’s hard across the board, but the greatest challenges we CURRENTLY face are uniquely concentrated within disorders and damage of the brain. For example, if you have a heart defect, we can measure such deficits clearly and in real time. While a drug may take time to work, many measurements of heart function can be obtained on demand. Similarly, if you have lung disease, we can measure how your lungs are functioning. If you have an eye disease, we can assess your vision. While none of these are comprehensive diagnostics for each tissue, they are valid and readily available means of assessing function. Assessing the function of an organic pump (heart), gas exchange (lungs), filter of toxins and metabolites (kidneys and liver) are by no means simple diagnostics. Yet, there are readily available means to assess the basic functions of these organs.
But what is the simple measure for function of the brain? Your brain does EVERYTHING! There really isn’t any one thing to distill into a basic functional assessment.
To further complicate things, the exact same injury or disease can manifest in a variety of different problems depending on the individual. For example, in multiple sclerosis, a newly formed lesion in one person may elicit speech and memory dysfunction. In a different patient a lesion may cause vision disturbances or mood disorders. Despite suffering from the same affliction, the functional deficits can vary widely making comparisons of symptom resolution extremely difficult to compare between patients. As a result, the difficulty in standardizing patient outcomes makes proving that a drug works very difficult, as no 2 patients are the same. So why is this important? Proving that a drug works requires being able to measure its benefit and proving statistically meaningful improvements. If you have any experience in statistics, you know how difficult this can be when you are measuring different things in different people. Measuring how well the heart pumps or how well lungs move air is drastically more straight forward then measuring how the brain…well how the brain does what? Which of the countless tasks that the brain is capable of do you choose? How can you measure improvements a drug makes in the brain when the symptoms are so complex and intricate?
What I’m trying to get at is, it’s really, really hard. Like overwhelmingly, intimidatingly, stupidly hard. And because of this, it’s intimidating, expensive, and complicated. But I have good news! It CAN be done! To do so, we have to recognize the difficulty of the journey ahead, the barriers that stand in our way, and what it will take to overcome it all and get where we want to go.
In our next article, we will further explore the individual institutions involved in developing new treatments and cures, and how they work together to spur medical advancement. This will begin the heart of the conversation where we can break down myth vs reality and discuss the new age of drug development and how this has evolved from the golden age of pharmaceutical science. All of this will builds towards understanding how the new system functions, and where advocates can intervene and support to achieve the best outcomes possible for patient health.
Check out the article as it originally appeared on MStranslate >
