Do You Have a Quiet H.E.R.O. In Your Portfolio Protecting & Fighting For You? [U.S. Global Leader in Simulations & Modeling Software for Drug Discovery & Development]
"What the world needs now is a quieter breed of hero, one actively fighting for a world in which rescues are no longer required." - Dan Heath
In his insightful book Upstream: How to Solve Problems Before They Happen that drew on insights from hundreds of interviews with unconventional problem solvers, Dan Heath shared that so often in life, we get stuck in a cycle of response. We put out fires. We deal with emergencies. We stay downstream, handling one problem after another, but we never make our way upstream to fix the systems that caused the problems. The police solve crimes, doctors treat patients with chronic illnesses, shelter is provided for the homeless. But we would all rather live in a world where crimes are not committed, diseases do not develop, and people do not lose their homes. So why do our efforts skew so heavily toward reaction rather than prevention? The need to prevent problems is perennial in our professional and daily lives, and we have the capacity to solve some of our thorniest issues - if only we start to think about the system rather than the symptoms. If only we start to think upstream.
Heath illuminated the vision that the world needs a quieter breed of UPSTREAM hero. UPSTREAM business models and strategies have also forged the enduring and exponential growth trajectory of our quiet H.E.R.O. innovators.
Case Story: U.S. Global Leader in Simulations & Modeling Software for Drug Discovery & Development
[Week (21-25 Sep): +9.4%]
Consider the UPSTREAM story of one of our portfolio companies in the Fund, the American global leader in simulations & modeling software for drug discovery & development, which is up 20.7% since the inception of the Fund on 28 August 2020, versus MSCI ACWI World index/NASDAQ -5.1%/-6.7% over the same period. The rising dividend-yielding company has also compounded 595% in capital gains in the recent 5 years vs MSCI ACWI World index +42.9%.
This software innovator solves the high-value problem for scientists in major pharmaceutical, biotechnology, agrochemical, cosmetics, food industry companies and regulatory agencies worldwide in rapidly predicting the properties and outcome of certain key potential drug dynamics and compound properties using machine-learning-based prediction of properties of molecules solely from their structure, thereby reducing the risk of multi-million dollar clinical trial failures, and reducing the time to market of effective new medications and scientific solutions. Regulatory agencies in the US and Europe are using and promoting the use of predictive technologies in order to streamline the drug approval process, reduce R&D costs, and potentially eliminate late stage drug failures. The company's software tools that enable clinicians to meet clinical trial endpoints could potentially save millions of dollars, as the prediction and data mining models can provide the researcher with a better understanding of drug reactions in the human body, enabling a more informed go/no-go decision, especially if a simulation software tool detects a failure prior to Phase III testing. 19 of the top 20 pharmaceutical companies, plus numerous mid- and small-sized companies, U.S. FDA and all major regulatory agencies, uses its software modeling & simulation technology.
The inspiring UPSTREAM story started with founders Mr. and Mrs. W who were also the pioneering inventors of Words+, the first integrated communication system based on a personal computer that was created in 1981, which radically transformed the way that people with disabilities and ALS (amyotrophic lateral sclerosis) could communicate and speak to their families again, including Cambridge University’s Professor Sir Stephen Hawking. Mr. W had created the system in response to an urgent personal need: his wife's mother was suffering from ALS. With his aerospace engineering background, Mr. W pioneered and managed the development of software for the simulation and automatic design optimization of a wide range of solid propellant rocket motors and missile systems, and was involved in modeling the early Space Shuttles for NASA. Mr. W went on to create the first simulation and modeling software for pharmaceutical research.
Co-founder Mr. W shared: "I first met Professor Sir Stephen Hawking in 1985, when my wife and I visited him at his office at Cambridge University. We had started Words+, Inc. in 1981 as a result of trying to make a communication system for my wife’s mother who had ALS from about 1978-1981. We had sent Stephen equipment earlier in 1985 to facilitate his communication, after tracheostomy surgery took away what little remaining speech he had. Words+ provided his equipment for his first public lecture in Chicago at the Texas Physics Conference. Through his suggestions, Stephen helped us to improve the system in a variety of ways over the years, both to communicate face-to-face and to write and deliver his many talks to groups of scientists and others. As an engineer with a keen interest in physics and especially the origins of the universe, I was delighted when he shared some of his papers with me. Stephen Hawking was a remarkable man and a global scientific leader. But he was also charming and witty, with a nice sense of humor. He would “dance” in his electric wheelchair at festive events, spinning in circles and dazzling all who watched. He made his place in history, along with Newton, Einstein, Bohr, and so many others. He will be missed.”
"My first aerospace job in 1971 was developing a computer program to simulate and optimize the ascent trajectory of the space shuttle to get the most payload into an orbit 150 nautical miles above the equator. In the early days, airplanes were put together with parts designed for other purposes (bicycles, farm equipment, textiles, automotive equipment, etc.). They were then flown by their brave designers to see if the design would work—often with disastrous results. Today, airplanes, helicopters, missiles, and rockets are designed in computers in a process that involves iterating through enormous numbers of designs before anything is made. Until very recently, novel drug-like molecules were nearly always made first like early airplanes, then tested to see if they were any good (although usually not on the brave scientists who created them!). The resulting extremely high failure rate is legendary."
"If we designed airplanes like we design drugs…Current simulation and modeling tools for drug discovery and development are very useful, and improvements are coming rapidly. Yet their adoption has taken 10–15 years to reach current usage levels, which remain well below where they are in other industries. There is no greater productivity tool than software. I’ll say that again—there is no greater productivity tool than software! The development costs for sophisticated simulation and modeling software are very high—in the tens millions of dollars for the more sophisticated programs. Like simulation and modeling software used in aerospace and other industries, the number of users is relatively small, making the cost per user much higher than for commercial software sold in huge quantities. The pharmaceutical industry is undergoing an awakening with respect to simulation and modeling tools. I predict that the day will come (probably not in my lifetime, but it will come) when pharmaceutical research and development will be so heavily driven by simulation and modeling tools that many fewer failures will occur in clinical and preclinical phases. Discovery efforts guided by de novo design tools available now offer the promise of more rapid discovery of good lead compounds and elimination of the majority of “losers” without the need to make and test them. Exploration of very large compound libraries automatically is already underway in a few organizations. I believe that many others will come to realize that simulation and modeling tools, properly applied, repay their costs many times over. For an industry that requires a long-term view of research and development, recognizing the value of predictive tools would seem to be a no-brainer.”