The combination of technology, biotechnology and new biotechnology will build a new bridge and build a new world.
Editor’s note: This article comes from WeChat public account “Outside the stack” (ID: zhanwai_) , author : Jorge Conde.
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In the traditional sense, technology and biology are irrelevant, and it is difficult to transform knowledge and experience into each other. But today, the intersection of biology, engineering, and computer science has blurred the boundaries of the traditional medical industry and created new biotechnology.
The article points out 16 misunderstandings of new biotechnology. For example, biotech companies can only be created by biotech venture capital, entrepreneurs with a scientific background cannot become CEOs, biotech companies can only be built on platforms, artificial intelligence Outdated viewpoints such as exaggerated, too early or too late to innovate in this field, and Silicon Valley not suitable for biotechnology development.
The author believes that it is necessary to combine technology, biotechnology, new biotechnology, and build a new bridge based on the old world to build a new world, which will bring new opportunities and bring revolutionary benefits to biology, technology and patients. influences.
Originally from A16Z, author Jorge Conde
Technology and biotechnology cannot be confused, at least traditionally. This partly explains why technology and biotechnology parted ways in the early 2000s. If a venture capital company owns the two companies at the same time, it will split them into two, or at least separate them. This approach makes sense.
Technical and biotech investors have different languages, and there is no need for a unified language. Biotechnology requires almost no troubleshooting procedures, and technology does not need to understand DNA. More importantly, in terms of the required capital, risk / return status, company construction and scale expansion models, the nature of the two investments is very different, and it is difficult to transform knowledge and experience into each other.
But nowadays, data and procedural biology are commonplace in today’s life sciences companies. Technology companies provide data workflows, core infrastructure and connective tissues across the entire medical value chain, from life sciences to care services. The old script that the clichés talk about is outdated, and the intersection of biology, computer science, and engineering blurs the boundaries of the entire medical industry. We call this hybrid of biotechnology and technology “newBiotechnology. “The world welcomes new biotechnology, and new biotechnology will upend the world.
New biotechnology is still questioned: Why are Silicon Valley venture capital companies investing in biotechnology? But it is wrong to ask this question. The real question is, in this new era of biotechnology, are conservative traditional technology companies or biotechnology companies the right investors to evaluate and support a new generation of companies in this field?
Here are 16 common myths and misconceptions about new biotechnology, which still exist in the fields of traditional technology and biotechnology. I will explain why these mindsets are outdated.
Biotech Ventures Establishes Biotech Company
Yes, a whole generation of biotech companies has been established by venture capital, creating real value for patients. But a new breed of bio-entrepreneurs has emerged in the intersection of biology, engineering, and computing, and they start their own companies instead of giving control to venture capital. This means that the role of venture capital must also change, to support rather than to command, to catalyze rather than create.
Science entrepreneurs cannot become CEOs
Traditional biotechnology believes that running a biotech company requires extensive experience in the pharmaceutical field. Indeed, experience is important, but as technology increasingly changes the way we discover and develop drugs, and even the nature of drugs, it is important to have a deep understanding of how to use powerful new technologies.
In emerging multi-disciplinary fields, such as artificial intelligence or bioengineering, a group of leading teachers and doctors have emerged, and they are already world-class experts in these fields. In many cases, entrepreneurs with these scientific backgrounds are actually more capable of driving innovation than veteran practitioners in the pharmaceutical field.
Biotech companies are built on the platform
Not usually. “Platforms” have been overused in biotechnology, and are often used to describe true depth of expertise in specific areas, such as cancer or neurodegenerative diseases. This departs from the standard definition of “platform” in technology, that is, the technical basis for developing other apps.
Next-generation biological companies are built on computing and engineering platforms that use proprietary technology to discover things that others cannot see or cannot do, such as creating detailed genetic circuit maps of cells or designing immune cells to attack cancer.
In other words, the biological platform provides you with technical knowledge or capability advantages (ideally both), and lays the foundation for the development of many future drugs. This is a huge leap forward over most traditional custom biotechnology platforms, which generate very few new drugs because discovery is not easy.
Artificial intelligence is exaggerated
When it comes to platforms, few are challenged by traditional biotechnology like artificial intelligence. Like any tool, artificial intelligence is certainly not a panacea. But it is particularly suitable to help us connect points in complex networks unimaginable in biology, which is beyond human ability.
Some of the most prominent experts in artificial intelligence are focusing their energy on health care, and many artificial intelligence startups and even mature pharmaceutical companies have emerged as data science companies and have increased their staff accordingly.
We are still in its infancy, and although it is sometimes hyped up, artificial intelligence has solved some clinical diagnostics and drug discovery conjectures.
Your innovation is too early
For any positive impact on treating patients, advances in biotechnology will take years to breathe. There is much hope and little time to cure patients. However, the technological innovation cycle in the biological field is accelerating, so commitment → potential → practice is developing at a record rate.
In less than a decade, the cost of DNA sequencing has decreased by at least 1,000 times, much faster than Moore’s Law, and it has now become a standard tool for R & D and diagnostics. The CRISPR used to edit human cells, which appeared only five years ago, has changed the way we develop, diagnose, and even treat diseases: in 2019, the first human clinical trial in the United States is underway, and more clinical trials are under development.
Your innovation is too late
Traditional biotechnology drug development follows an antiquated line. Once a new disease target is identified, it is a “molecular race.” “If you can’t reach the goal in the shortest time, then you must achieve the highest quality when you reach the goal.” If you fail like many people, you must clear everything from the next time and start again.
However, with the help of engineering biology, we can create generations of technology based on previous successes and limitations. Just like the software version. A new generation of immunotherapy CAR T is being built on the first generation. And the modular aspect of these drugs, the ability to reuse and slightly modify common ingredients, means that new applications are easier to build. The structure of the original gene editing technology CRISPR-Cas9 has been remixed and imagined, bringing new features and functions. As a result, the innovation cycle is not only accelerating, it is also mixing.
Evolving is biotechnology, not new biotechnology
Some people think that the new era has not yet come, and what we are seeing now is only the continuous progress of biotechnology. However, when progress is large enough, evolution itself will evolve into a revolution, and steady development will give way to huge changes. In the past few years, we have entered the era of programmable drugs, which can design organisms as gene and cell therapies. We also programmed digital therapies.
Everything is moving fast, and the FDA is committed to modernizing and reforming to stay ahead. The FDA even provides guidance for the learning and development of medical artificial intelligence. Everything is ready, and entrepreneurs tired of the status quo are reshaping the industry and disrupting the long-established business model.The significance of new biotechnology is beyond the scope of human health. Engineering biology is changing a range of industries from food to fashion, with the potential to change everything. If this process is regarded as “evolution”, it must be the era of the Cambrian explosion.
You can’t build a technology company Build a biotechnology company
This statement is partially true. The new biotechnology company mixes traditional and biotechnologies, with both graduate object laboratories and companies responsible for data and design. Establishing a new biotechnology company needs to be able to merge previously fragmented disciplines, such as engineering, to promote multidisciplinary integration, to iterate technology with an open mindset, and to promote continuous improvement.
As my partner, Mark Anderson, said: “Moore’s Law is the goal, not the prediction.” Like the technology industry, sharing infrastructure like lab space and AWS has greatly reduced the need to start a bio startup. Cost and time.
You cannot make scientific discoveries
When dealing with biological problems, because the working system is not designed by ourselves, we are at a significant disadvantage. But everything is progressing and the rules of the game have changed. The current platform can observe biology with unprecedented breadth and resolution. The DNA sequencer is an engineering marvel. Advanced artificial intelligence systematically solves biological complexity and realizes industrialization. Perhaps most importantly, biological engineering programs biological systems directly. All this brings us into a world where scientific discovery can and should be made and brings us closer to purposeful biological design.
Regulatory risk is binary
It is critical to ensure the safety and effectiveness of any new drug. Once you put a certain drug into the body, everything is heaven, and it is well known that clinical trial failure rates are 90%.
However, the FDA may not approve your drug, which the industry calls regulatory risk. This statement is wrong. In fact, this is a substitute for scientific risk, that is, your medicine does not work. In a world where it’s unclear whether your target can regulate disease and / or your molecules hit the target adequately and completely, the risk feels like flipping a coin, right or wrong.
However, if the cause of the disease is clear, just like a genetic disease, then an engineering solution is not binary. You can iterate component by component to achieve success. Once we know how to pass one gene to one cell type for a given disease, it’s easier to pass another gene to another cell to treat another disease.
The risk of reimbursement is great
In health care, reimbursement is definitely at the core of the market entry plan, largely because end users (patients) are different from payers (insurers, employers, governments). But the term “reimbursement risk” is also incorrect, confusing and obscuring the strict process of ensuring reimbursement and actual risks.The actual risk is that a compelling value proposition cannot be proven in the first place.
It is difficult to prove that a new treatment method can significantly improve the existing method. However, as programmable medicines become more complex, we may be able to treat the most serious illnesses, save lives, and avoid downstream costs, thereby reducing the risk of reimbursement. Instead, making reimbursement an obligation to fair costs and benefits Assigned to all stakeholders.
It takes too long to create value in the field of biotechnology, and the cost is not low
There is no doubt that developing new drugs is much more expensive than developing software products. In traditional biotechnology, the change in value is largely a step function: it can only be known if the drug is effective after it has been tested on many patients after years of testing and spent millions of dollars testing.
Engineering methods have the potential for smoother, more linear value creation. Taking gene editing as an example, you can patch up the CRISPR system until it works, starting with repairing errors that cause disease and starting with in vitro applications, significantly reducing scientific risk. If a small-scale experiment is needed before it has a significant impact, the scale is small but significant. Of course, this process is still costly and laborious, but these biotech companies have the potential to iterate and generate more proof and value in the process.
Silicon Valley’s “Quick Action, Breaking the Rules” attitude Doesn’t Work in the Medical Industry
“Quick action, break the rules” is a rough suggestion. Despite the right time and the ability to take risks, Silicon Valley also has a lot of experience in dealing with difficult issues. Silicon Valley can make satellites, launch rockets, and use technology to fundamentally change a range of stagnant industries, from cars to music to movie production.
Some of these innovations are for entertainment and some are for defense. If Silicon Valley is incapable of taking health care seriously, it is good to say that the argument lacks information to prove it, and to be bad is actually contrary to reality.
Theranos, a scammer, was created by Silicon Valley Ventures
But this is not the case. In fact, no venture capital firm has invested heavily in this blood testing company. Investors cannot conduct due diligence on the company and its technology. In addition to personal relationships, the company does not have senior directors or consultants from the technology or biotechnology field. Theranos is a “Silicon Valley company” simply because of its geographical location.
Everywhere you go, excellent biotech ventures need to conduct in-depth investigations, including field trips, background checks, data analysis, intellectual property audits, and even blind sample detection. During the process of due diligence, problems often arise, but the inability to conduct due diligence in the beginning is a red flag.
Silicon Valley cannot do biotechnology
This statement ignores the fact that the earliest and most successful in historyGenentech was born here. Genentech has left a rich legacy that has enabled today’s South San Francisco and the surrounding bay area to have a thriving ecosystem, both mature biotech companies and next-generation biocompanies.
And there are more startups in the area. Together with A16Z, seed companies, early and late venture capital companies form a rich ecosystem focused on new biotechnology. Just like the founders of the new biotechnology they support, these investors are becoming more diverse, with computer scientists, bioengineers, medical doctors, executives from former biopharmaceutical companies, and seasoned healthcare entrepreneurs.
Stand on your track
Should technology and biotechnology be parallel and non-intersecting? Maybe so, but when the two merge, it’s hard to keep track. The good news is that this road is long and tortuous, spanning different worlds, bringing new opportunities and revolutionizing biology, technology and patients.
It is true that some fields are suitable for traditional biotechnology and some are more suitable for new biotechnology. However, there are parallel intersections, combining technology, biotechnology, and new biotechnology. Based on the old world, a new bridge is built to create a new world.
Some people think that the new era has not yet come, and what we are seeing now is only the continuous progress of biotechnology. However, when progress is large enough, evolution itself will evolve into a revolution, and steady development will give way to huge changes. In the past few years, we have entered the era of programmable drugs, which can design organisms as gene and cell therapies. We also programmed digital therapies.
Everything is moving fast, and the FDA is committed to modernizing and reforming to stay ahead. The FDA even provides guidance for the learning and development of medical artificial intelligence. Everything is ready, and entrepreneurs tired of the status quo are reshaping the industry and disrupting the long-established business model.The significance of new biotechnology is beyond the scope of human health. Engineering biology is changing a range of industries from food to fashion, with the potential to change everything. If this process is regarded as “evolution”, it must be the era of the Cambrian explosion.
You can’t build a technology company Build a biotechnology company
This statement is partially true. The new biotechnology company mixes traditional and biotechnologies, with both graduate object laboratories and companies responsible for data and design. Establishing a new biotechnology company needs to be able to merge previously fragmented disciplines, such as engineering, to promote multidisciplinary integration, to iterate technology with an open mindset, and to promote continuous improvement.
As my partner, Mark Anderson, said: “Moore’s Law is the goal, not the prediction.” Like the technology industry, sharing infrastructure like lab space and AWS has greatly reduced the need to start a bio startup. Cost and time.
You cannot make scientific discoveries
When dealing with biological problems, because the working system is not designed by ourselves, we are at a significant disadvantage. But everything is progressing and the rules of the game have changed. The current platform can observe biology with unprecedented breadth and resolution. The DNA sequencer is an engineering marvel. Advanced artificial intelligence systematically solves biological complexity and realizes industrialization. Perhaps most importantly, biological engineering programs biological systems directly. All this brings us into a world where scientific discovery can and should be made and brings us closer to purposeful biological design.
Regulatory risk is binary
It is critical to ensure the safety and effectiveness of any new drug. Once you put a certain drug into the body, everything is heaven, and it is well known that clinical trial failure rates are 90%.
However, the FDA may not approve your drug, which the industry calls regulatory risk. This statement is wrong. In fact, this is a substitute for scientific risk, that is, your medicine does not work. In a world where it’s unclear whether your target can regulate disease and / or your molecules hit the target adequately and completely, the risk feels like flipping a coin, right or wrong.
However, if the cause of the disease is clear, just like a genetic disease, then an engineering solution is not binary. You can iterate component by component to achieve success. Once we know how to pass one gene to one cell type for a given disease, it’s easier to pass another gene to another cell to treat another disease.
The risk of reimbursement is great
In health care, reimbursement is definitely at the core of the market entry plan, largely because end users (patients) are different from payers (insurers, employers, governments). But the term “reimbursement risk” is also incorrect, confusing and obscuring the strict process of ensuring reimbursement and actual risks.The actual risk is that a compelling value proposition cannot be proven in the first place.
It is difficult to prove that a new treatment method can significantly improve the existing method. However, as programmable medicines become more complex, we may be able to treat the most serious illnesses, save lives, and avoid downstream costs, thereby reducing the risk of reimbursement. Instead, making reimbursement an obligation to fair costs and benefits Assigned to all stakeholders.
It takes too long to create value in the field of biotechnology, and the cost is not low
There is no doubt that developing new drugs is much more expensive than developing software products. In traditional biotechnology, the change in value is largely a step function: it can only be known if the drug is effective after it has been tested on many patients after years of testing and spent millions of dollars testing.
Engineering methods have the potential for smoother, more linear value creation. Taking gene editing as an example, you can patch up the CRISPR system until it works, starting with repairing errors that cause disease and starting with in vitro applications, significantly reducing scientific risk. If a small-scale experiment is needed before it has a significant impact, the scale is small but significant. Of course, this process is still costly and laborious, but these biotech companies have the potential to iterate and generate more proof and value in the process.
Silicon Valley’s “Quick Action, Breaking the Rules” attitude Doesn’t Work in the Medical Industry
“Quick action, break the rules” is a rough suggestion. Despite the right time and the ability to take risks, Silicon Valley also has a lot of experience in dealing with difficult issues. Silicon Valley can make satellites, launch rockets, and use technology to fundamentally change a range of stagnant industries, from cars to music to movie production.
Some of these innovations are for entertainment and some are for defense. If Silicon Valley is incapable of taking health care seriously, it is good to say that the argument lacks information to prove it, and to be bad is actually contrary to reality.
Theranos, a scammer, was created by Silicon Valley Ventures
But this is not the case. In fact, no venture capital firm has invested heavily in this blood testing company. Investors cannot conduct due diligence on the company and its technology. In addition to personal relationships, the company does not have senior directors or consultants from the technology or biotechnology field. Theranos is a “Silicon Valley company” simply because of its geographical location.
Everywhere you go, excellent biotech ventures need to conduct in-depth investigations, including field trips, background checks, data analysis, intellectual property audits, and even blind sample detection. During the process of due diligence, problems often arise, but the inability to conduct due diligence in the beginning is a red flag.
Silicon Valley cannot do biotechnology
This statement ignores the fact that the earliest and most successful in historyGenentech was born here. Genentech has left a rich legacy that has enabled today’s South San Francisco and the surrounding bay area to have a thriving ecosystem, both mature biotech companies and next-generation biocompanies.
And there are more startups in the area. Together with A16Z, seed companies, early and late venture capital companies form a rich ecosystem focused on new biotechnology. Just like the founders of the new biotechnology they support, these investors are becoming more diverse, with computer scientists, bioengineers, medical doctors, executives from former biopharmaceutical companies, and seasoned healthcare entrepreneurs.
Stand on your track
Should technology and biotechnology be parallel and non-intersecting? Maybe so, but when the two merge, it’s hard to keep track. The good news is that this road is long and tortuous, spanning different worlds, bringing new opportunities and revolutionizing biology, technology and patients.
It is true that some fields are suitable for traditional biotechnology and some are more suitable for new biotechnology. However, there are parallel intersections, combining technology, biotechnology, and new biotechnology. Based on the old world, a new bridge is built to create a new world.
There is no doubt that developing new drugs is much more expensive than developing software products. In traditional biotechnology, the change in value is largely a step function: it can only be known if the drug is effective after it has been tested on many patients after years of testing and spent millions of dollars testing.
Engineering methods have the potential for smoother, more linear value creation. Taking gene editing as an example, you can patch up the CRISPR system until it works, starting with repairing errors that cause disease and starting with in vitro applications, significantly reducing scientific risk. If a small-scale experiment is needed before it has a significant impact, the scale is small but significant. Of course, this process is still costly and laborious, but these biotech companies have the potential to iterate and generate more proof and value in the process.