AI is changing the field of synthetic biology and how we engineer biology. Its helping engineers design new ways to design genetic circuits -- and it could leave a remarkable impact on the future of humanity
TVs and radios blare that artificial intelligence is coming, and it will take your job and beat you at chess.
But AI is already here, and it can beat you and the worlds best at chess. In2012, it was also used by Google to identify cats in YouTube videos. Today, its the reason Teslas have Autopilot and Netflix and Spotify seem to read your mind. Now, AI is changing the field of synthetic biology and how we engineer biology. Its helping engineers design new ways to design genetic circuits and it could leave a remarkable impact on the future of humanity through the huge investment it has been receiving ($12.3b in the last 10 years) and the markets it is disrupting.
The idea of artificial intelligence is relatively straightforward it is the programming of machines with reasoning, learning, and decision-making behaviors. Some AI algorithms (which are just a set of rules that a computer follows) are so good at these tasks that they can easily outperform human experts.
Most of what we hear about artificial intelligence refers to machine learning, a subclass of AI algorithms that extrapolate patterns from data and then use that analysis to make predictions. The more data these algorithms collect, the more accurate their predictions become. Deep learning is a more powerful subcategory of machine learning, where a high number of computational layers called neural networks (inspired by the structure of the brain) operate in tandem to increase processing depth, facilitating technologies like advanced facial recognition (including FaceID on your iPhone).
[For a more detailed explanation of artificial intelligence and its various subcategories, check out this article and its flowchart.]
Regardless of the type of AI, or its application, we are in the midst of a computational revolution that is extending its tendrils beyond the computer world. Soon, AI will impact the medicines you take, the fuels you burn, and even the detergents that you use to wash your clothes.
Biology, in particular, is one of the most promising beneficiaries of artificial intelligence. From investigating genetic mutations that contribute to obesity to examining pathology samples for cancerous cells, biology produces an inordinate amount of complex, convoluted data. But the information contained within these datasets often offers valuable insights that could be used to improve our health.
In the field of synthetic biology, where engineers seek to rewire living organisms and program them with new functions, many scientists are harnessing AI to design more effective experiments, analyze their data, and use it to create groundbreaking therapeutics. Here are five companies that are integrating machine learning with synthetic biology to pave the way for better science and better engineering.
(Oakland, CA, founded in 2014, has raised $24.9M)
Machine learning algorithms must begin with large amounts of data but, in biology, good data is incredibly challenging to produce because experiments are time-consuming, tedious and hard to replicate. Fortunately, one company is addressing this bottleneck by making it easier for scientists to do exactly that.
Riffyns cloud-based software platform helps researchers standardize, define, and perform experiments and streamlines data analysis, which enables researchers to focus on doing the actual science and makes the use machine learning algorithms to extract deeper insights from their experiments an everyday reality.
With this platform, experiments can be conducted more efficiently, leading to massive decreases in cost, improvements in productivity and quality, and data that is primed to be further analyzed with sophisticated machine learning techniques. That means companies can use this technology to develop new proteins for cancer therapeutics, and they can do it much faster and better than before. Riffyn already works with 8 of the top 15 global biotech and biopharma firms and they were founded just five years ago.
(Cambridge, UK, officially launched in 2019)
There are a lot of moving parts in the synthetic biology world, which makes it difficult but vital to streamline and integrate operations as much as possible. For the last decade, the computational biology arm of Microsoft Research, Station B, has been developing machine learning models for biology to fix this problem and expedite research across a variety of fields, from medicine to construction.
Its efforts are paying off in the form of various new partnerships, too. With Synthace, it is developing software to automate and expedite experiments in the lab. Station B is additionally working with Princeton to research the mechanisms behind biofilms (relevant to how bacterial colonies develop antibiotic resistance) by utilizing machine learning-based methods that extract patterns from images taken during different stages of bacterial growth. Station B is also collaborating with Oxford Biomedica, a company harnessing these machine learning capabilities to improve a promising gene therapy for leukemia and lymphoma. This is perhaps one of synthetic biologys biggest areas for impact: designing therapeutics to combat a variety of diseases.
(Based in San Francisco, CA, founded in 2012, has raised $51M)
Atomwise is tackling drug development with their deep-learning platform, called AtomNet, that can rapidly model molecular structures. It can accurately analyze chemical interactions within small molecules to predict the efficacy of targeting diseases ranging from Ebola to multiple sclerosis. By utilizing data about atomic structure, Atomwise designs novel therapeutics that would otherwise be nearly impossible to develop.
They have numerous academic and corporate partnerships with institutions including Charles River Laboratories, Merck, University of Toronto, and Duke University School of Medicine, that are providing many of the real-world applications and opportunities to drive this research forward. They also recently announced an up-to $1.5B collaboration with the Jiangsu Hansoh Pharmaceutical Group, the Chinese company with one of this years biggest biopharma IPOs.
While Atomwises approach to designing molecules is powerful and well on its way to combatting multiple diseases, there is no one perfect method to computational discovery. Thats where Arzeda comes in.
(Seattle, WA, founded in 2008, has raised $15.2M)
Arzeda, a company originating from the Baker Lab at the University of Washington, uses its protein design platform (rooted, of course, in machine learning algorithms) to engineer proteins for everything from industrial enzymes to crops and their microbiomes.
Arzeda builds its molecules entirely from scratch (or de novo), rather than optimize existing ones, to perform new functions not found anywhere in nature; deep learning techniques are vital to ensure the proteins they design fold correctly (a very computationally demanding problem) and function as intended. Once the computational steps are complete, the new proteins are produced through fermentation (just like beer), bypassing natural evolution to efficiently produce brand-new molecules.
(South San Francisco, CA, founded in 2012, self-funded by licensing technologies)
On the other end of the design spectrum, Distributed Bio harnesses rational protein engineering to optimize existing antibodies, which are the proteins in your body that detect bacteria and fight off other disease-causing invaders, to create novel therapeutics.
Among the many immunology-engineering technologies that the company boasts (from a universal flu vaccine to a broad-coverage snake antivenom) is the Tumbler platform. Using machine learning methods, Tumbler creates over 500 million variations of a starting antibody to expand and quantify the search space of what changes to the molecule are most valuable; then, it scores sequences to predict how well they bind to their target in real life and uses the valuable change information to further improve the best-scoring sequences. The production cycle continues as the top sequences are synthesized and tested in the lab. Eventually, an archetypal molecule emerges to fulfill the intended therapeutic purpose something not necessarily observed in nature, but combining all of the best possible characteristics.
Tumbler has helped to enable a wide range of applications beyond traditional single-target drug development from designing antibodies that bind to multiple targets simultaneously to creating chimeric antigen receptor T-cell (CAR-T) therapies (together with Chimera Bioengineering) for cancer treatments with reduced toxicity, the power of this end-to-end optimization platform to generate ideal antibodies at scale is unprecedented.
While this progress is exciting, artificial intelligence is not a universal replacement for our investigations of the natural world, nor is it the only way to develop cures for human diseases. At times, it may not be technically useful or even ethically sound. As we continue to reap the benefits of this technology and increasingly incorporate it into our daily lives, we must continue having conversations about the design, implementation, and ethics of innovations in synthetic biology and AI; we stand on the precipice of a new age for science and humanity.
Thanks to Aishani Aatresh for additional research and reporting in this article. Aishani is also a researcher at Distributed Bio developing computational immunoengineering methods to generate superior antibodies. Please note: I am the founder of SynBioBeta, the innovation network for the synthetic biology industry, and some of the companies that I write about are sponsors of the SynBioBeta conference (click here for a full list of sponsors).
Continued here:
Meet Five Synthetic Biology Companies Using AI To Engineer Biology - Forbes
- Classic reasoning systems like Loom and PowerLoom vs. more modern systems based on probalistic networks - November 8th, 2009 [November 8th, 2009]
- Using Amazon's cloud service for computationally expensive calculations - November 8th, 2009 [November 8th, 2009]
- Software environments for working on AI projects - November 8th, 2009 [November 8th, 2009]
- New version of my NLP toolkit - November 8th, 2009 [November 8th, 2009]
- Semantic Web: through the back door with HTML and CSS - November 8th, 2009 [November 8th, 2009]
- Java FastTag part of speech tagger is now released under the LGPL - November 8th, 2009 [November 8th, 2009]
- Defining AI and Knowledge Engineering - November 8th, 2009 [November 8th, 2009]
- Great Overview of Knowledge Representation - November 8th, 2009 [November 8th, 2009]
- Something like Google page rank for semantic web URIs - November 8th, 2009 [November 8th, 2009]
- My experiences writing AI software for vehicle control in games and virtual reality systems - November 8th, 2009 [November 8th, 2009]
- The URL for this blog has changed - November 8th, 2009 [November 8th, 2009]
- I have a new page on Knowledge Management - November 8th, 2009 [November 8th, 2009]
- N-GRAM analysis using Ruby - November 8th, 2009 [November 8th, 2009]
- Good video: Knowledge Representation and the Semantic Web - November 8th, 2009 [November 8th, 2009]
- Using the PowerLoom reasoning system with JRuby - November 8th, 2009 [November 8th, 2009]
- Machines Like Us - November 8th, 2009 [November 8th, 2009]
- RapidMiner machine learning, data mining, and visualization tool - November 8th, 2009 [November 8th, 2009]
- texai.org - November 8th, 2009 [November 8th, 2009]
- NLTK: The Natural Language Toolkit - November 8th, 2009 [November 8th, 2009]
- My OpenCalais Ruby client library - November 8th, 2009 [November 8th, 2009]
- Ruby API for accessing Freebase/Metaweb structured data - November 8th, 2009 [November 8th, 2009]
- Protégé OWL Ontology Editor - November 8th, 2009 [November 8th, 2009]
- New version of Numenta software is available - November 8th, 2009 [November 8th, 2009]
- Very nice: Elsevier IJCAI AI Journal articles now available for free as PDFs - November 8th, 2009 [November 8th, 2009]
- Verison 2.0 of OpenCyc is available - November 8th, 2009 [November 8th, 2009]
- What’s Your Biggest Question about Artificial Intelligence? [Article] - November 8th, 2009 [November 8th, 2009]
- Minimax Search [Knowledge] - November 8th, 2009 [November 8th, 2009]
- Decision Tree [Knowledge] - November 8th, 2009 [November 8th, 2009]
- More AI Content & Format Preference Poll [Article] - November 8th, 2009 [November 8th, 2009]
- New Planners Solve Rescue Missions [News] - November 8th, 2009 [November 8th, 2009]
- Neural Network Learns to Bluff at Poker [News] - November 8th, 2009 [November 8th, 2009]
- Pushing the Limits of Game AI Technology [News] - November 8th, 2009 [November 8th, 2009]
- Mining Data for the Netflix Prize [News] - November 8th, 2009 [November 8th, 2009]
- Interview with Peter Denning on the Principles of Computing [News] - November 8th, 2009 [November 8th, 2009]
- Decision Making for Medical Support [News] - November 8th, 2009 [November 8th, 2009]
- Neural Network Creates Music CD [News] - November 8th, 2009 [November 8th, 2009]
- jKilavuz - a guide in the polygon soup [News] - November 8th, 2009 [November 8th, 2009]
- Artificial General Intelligence: Now Is the Time [News] - November 8th, 2009 [November 8th, 2009]
- Apply AI 2007 Roundtable Report [News] - November 8th, 2009 [November 8th, 2009]
- What Would You do With 80 Cores? [News] - November 8th, 2009 [November 8th, 2009]
- Software Finds Learning Language Child's Play [News] - November 8th, 2009 [November 8th, 2009]
- Artificial Intelligence in Games [Article] - November 8th, 2009 [November 8th, 2009]
- Artificial Intelligence Resources - November 8th, 2009 [November 8th, 2009]
- Alan Turing: Mathematical Biologist? - April 25th, 2012 [April 25th, 2012]
- BBC Horizon: The Hunt for AI ( Artificial Intelligence ) - Video - April 30th, 2012 [April 30th, 2012]
- Can computers have true artificial intelligence" Masonic handshake" 3rd-April-2012 - Video - April 30th, 2012 [April 30th, 2012]
- Kevin B. Korb - Interview - Artificial Intelligence and the Singularity p3 - Video - April 30th, 2012 [April 30th, 2012]
- Artificial Intelligence - 6 Month Anniversary - Video - April 30th, 2012 [April 30th, 2012]
- Science Breakthroughs - April 30th, 2012 [April 30th, 2012]
- Hitman: Blood Money - Part 49 - Stupid Artificial Intelligence! - Video - April 30th, 2012 [April 30th, 2012]
- Research Members Turned Off By HAARP Artificial Intelligence - Video - April 30th, 2012 [April 30th, 2012]
- Artificial Intelligence Lecture No. 5 - Video - April 30th, 2012 [April 30th, 2012]
- The Artificial Intelligence Laboratory, 2012 - Video - April 30th, 2012 [April 30th, 2012]
- Charlie Rose - Artificial Intelligence - Video - April 30th, 2012 [April 30th, 2012]
- Expert on artificial intelligence to speak at EPIIC Nights dinner - May 4th, 2012 [May 4th, 2012]
- Filipino software engineers complete and best thousands on Stanford’s Artificial Intelligence Course - May 4th, 2012 [May 4th, 2012]
- Vodafone xone™ Hackathon Challenges Developers and Entrepreneurs to Build a New Generation of Artificial Intelligence ... - May 4th, 2012 [May 4th, 2012]
- Rocket Fuel Packages Up CPG Booster - May 4th, 2012 [May 4th, 2012]
- 2 Filipinos finishes among top in Stanford’s Artificial Intelligence course - May 5th, 2012 [May 5th, 2012]
- Why Your Brain Isn't A Computer - May 5th, 2012 [May 5th, 2012]
- 2 Pinoy software engineers complete Stanford's AI course - May 7th, 2012 [May 7th, 2012]
- Percipio Media, LLC Proudly Accepts Partnership With MIT's Prestigious Computer Science And Artificial Intelligence ... - May 10th, 2012 [May 10th, 2012]
- Google Driverless Car Ok'd by Nevada - May 10th, 2012 [May 10th, 2012]
- Moving Beyond the Marketing Funnel: Rocket Fuel and Forrester Research Announce Free Webinar - May 10th, 2012 [May 10th, 2012]
- Rocket Fuel Wins 2012 San Francisco Business Times Tech & Innovation Award - May 13th, 2012 [May 13th, 2012]
- Internet Week 2012: Rocket Fuel to Speak at OMMA RTB - May 16th, 2012 [May 16th, 2012]
- How to Get the Most Out of Your Facebook Ads -- Rocket Fuel's VP of Products, Eshwar Belani, to Lead MarketingProfs ... - May 16th, 2012 [May 16th, 2012]
- The Digital Disruptor To Banking Has Just Gone International - May 16th, 2012 [May 16th, 2012]
- Moving Beyond the Marketing Funnel: Rocket Fuel Announce Free Webinar Featuring an Independent Research Firm - May 23rd, 2012 [May 23rd, 2012]
- MASA Showcases Latest Version of MASA SWORD for Homeland Security Markets - May 23rd, 2012 [May 23rd, 2012]
- Bluesky Launches Drones for Aerial Surveying - May 23rd, 2012 [May 23rd, 2012]
- Artificial Intelligence: What happened to the hunt for thinking machines? - May 25th, 2012 [May 25th, 2012]
- Bubble Robots Move Using Lasers [VIDEO] - May 25th, 2012 [May 25th, 2012]
- UHV assistant professors receive $10,000 summer research grants - May 27th, 2012 [May 27th, 2012]
- Artificial intelligence: science fiction or simply science? - May 28th, 2012 [May 28th, 2012]
- Exetel taps artificial intelligence - May 29th, 2012 [May 29th, 2012]
- Software offers brain on the rain - May 29th, 2012 [May 29th, 2012]
- New Dean of Science has high hopes for his faculty - May 30th, 2012 [May 30th, 2012]
- Cognitive Code Announces "Silvia For Android" App - May 31st, 2012 [May 31st, 2012]
- A Rat is Smarter Than Google - June 5th, 2012 [June 5th, 2012]