Very little about drug development is efficient. The failure rate for drugs making their way to commercialization is 90%, after which more than around $1 billion and 10 years is sunk into each one on average.

But technological advancements in data collection are propelling artificial intelligence in drug discovery, which may unlock the ability to find cures for diseases that evaded the scientific community for centuries.��

So far this year, startups in drug discovery raised more than $1.4 billion, according to Crunchbase data.

One of these startupsthem is , an AI drug discovery platform founded by Jacob and in 2018.

“There are thousands of problems sitting out there that we don’t know the answer for. Thousands and thousands,” said Berlin. “So having a platform that lets us go faster, be precise and scale can really transform the opportunities in front of us.”

How drug discovery currently works

Current processes of drug discovery are long and tedious. Scientists in academia or pharma make molecules. They look for “targets” (like proteins) the molecule can swim to in the body and deliver therapy.��

To do that, scientists need to make sure the molecule doesn’t mistake a healthy protein for a target, otherwise a drug swimming around in the body may attach to and kill a healthy cell—amounting to poison. Once scientiststhey get a target, it’s taken out of the body and tested against molecules in the lab to see what will stick.��

But as clinical trials continue, several of those drugs fail due to unintended toxicity in the rest of the body, or the drug itself working in the lab but not in humans. With those failures, it sinks millions of dollars and years of research are lost..

“It’s just this huge funnel where stuff can drop out at any point in time,” said , a partner at who invests in health startups. “And I think that the problems are very much at the very, very, very beginning of this process.”

Terray and platforms like it work differently. Terray compares molecules against targets, and the AI assesses what parts of the molecule correlate strongly with the target. Terray can then make new molecules that correlate even more strongly, refining it.��

Through leveraging data, drug discovery platforms can better predict outcomes of drugs at the start of the process. AI matches molecules with targets and simulates how it will work in the body, giving it a better chance of surviving clinical trials and lowering toxicity rates in patients.

“At the end of the day, it’s about innovation and trying to find interesting, novel ways of treating some really unmet medical needs,” said , a biotech investor and managing general partner at .

Pharma bets on early-stage technology

AI drug discovery is still nascent, and will require interdisciplinary knowledge of chemistry, computational engineering, machine learning and biology. Data collection in drug development only became popular in 2017, a shift we see in funding: Between 2017 and 2018, funding increased by 190%.�� 

“The foundational layers in terms of data generation were just not there for a long time,” Choi said. “In the last few years we have not seen the breadth of it. We’re just starting a data revolution.”

Nevertheless, large pharma companies like are betting big on this tech to accelerate the pace of drug development, raising profits and getting medicines into the market faster. Many pharma companies partner with AI drug discovery platforms. For example, Earlier this year, and .��

“The molecules that come out of the drug discovery as a result of AI, there’s only a few in clinical development right now,” Crean said. “It sounds kind of Star Trek-y. Yes, it sounds exciting, but I think we just have to try and manage our expectations.”

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Other investors in this round include , Scale Ventures and .

We spoke with co-founder and CEO about the fast-growing company that has raised close to $100 million in three years.��

Flatfile has “expanded across enterprises, Fortune 500s, and our objective is to be part of every data exchange in the world,” said Boskovic.

Wide range of customers

The one surprising fact about this ETL (extract, transform, load) solution is that the company does not typically sell to chief information officers, but more often to product and implementation teams who need to manage vendor or customer relationships.��

“The problem with data exchange at the edge of the business is that every customer is bringing something different,” said Boskovic on its customers like collecting real estate data from brokers or with accountants uploading client data. Data that is not accurate creates problems over time that can take weeks or months to address with customers going back and forth. “Flatfile automates that manual labor, that process, and just makes it drag and drop,” he said.��

From a revenue perspective, the company went from zero to $1 million in ARR in its first year, then close to $4 million in its second year, and is now tracking to 2x to 3x growth in its third year of revenue.

The company’s 500 customers include enterprise SaaS company , and .��

Flatfile’s customer fees range from free for companies with five to 10 employees who are just getting started, to a few thousand dollars, then all the way up to $500,000. Their largest customers pay well into the millions.��

“We started off initially as a button that could be added to a software allowing users to import data quickly. That button has grown to be an entire platform,” said Boskovic.

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On Tuesday, the companies announced they will renew their partnership with a $20 million equity investment from Pfizer that is projected to net $110 million over five years.

CytoReason is an artificial intelligence-powered disease model platform that speeds up drug discovery. It uses data to simulate different diseases on models of cells or tissue, which can help drug companies see the effects of different or molecules on the model and speed up drug discovery.

This shaves precious time off the long and arduous process of getting a drug to market for patients, while allowing drug companies to make more money off their therapeutics at a fraction of the cost.

The platform-pharma partnership

Israel-based CytoReason is a platform, one of many that are becoming the darlings of venture capital firms for their ability to make money while they incubate by partnering with big pharmaceutical companies. This is a stark contrast to most drug-focused startups, which can spend roughly a decade and nearly a billion dollars before they can go to market and make a return on investment.��

“One of the pharma organizations that hasn’t had a great R&D organization themselves says, ‘Hey, this is a unique game-changing way to discover new drugs. Maybe I should just buy the whole platform,’” said , COO and CFO of early-stage biotech investment firm .

This leg-up is exceptionally important for investors as the market downturn forced biotech companies to extend their runways with scant venture investment. Partnerships often act as a source of funding from large pharmaceutical companies when venture firms tighten their purse strings.

Platforms are slowly rising in the ranks of venture investment, making up roughly 35% of all biotech investment so far in 2022, per Crunchbase data. The year prior, that number was 28%.��

CytoReason has partnered with several large pharma companies since it got its start in 2016, including and last year. But it’s far from the only one to do so. In 2021, California-based inked a deal with worth up to $875 million (according to both companies) , bringing them to the patients faster.

“While we see the market still down, we know that there are large pharmas out there who are ready to absorb innovations and acquire and develop and partner on innovative biotech technology,” said , the health-focused partner at .��

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The SF-based startup has raised $100M, bringing its total known funding to $170M. And with the check comes a mission beyond rows and columns in a spreadsheet: an aim to democratize software.

, Airtable’s CEO and co-founder, told Crunchbase News that his startup aims to take “all of the complexities of interacting with a relational database and exposing those to an end-user in the most intuitive possible form.” Essentially, Liu is saying that if you can grok Excel, you should be able to grok Airtable.

However, manipulating that data into a product or useful piece of software mostly remains in the domain of developers. That doesn’t mean some companies haven’t tried making building apps on top of databases easier. , which automates workflows for hundreds of SMBs across the nation, also boasts about its ability to make software creation accessible to end users. But according to Liu, Quickbase and other drag-and-drop software creation tools are more “low-code app platforms that are frankly never going to see bottoms-up adoption.”

“If you showed Quickbase to twenty randomly selected people from a company or a cross-section of America, I think zero out of twenty, more times than not, would be able to go or want to go build the application they need on top of Quickbase,” Liu explained, crediting Airtable’s more considered approach to product development as a big part of its differentiation from more established players.

Furthermore, Liu doesn’t believe that an injection of cash dwarfing all of its prior total funding rounds will impact the company’s ability to execute on new, user-friendly features.

“We were deliberate about thinking through who are the right people to involve at this stage to help us scale to the next five levels of the company,” Liu explained. That said, investors do like cash as much as they like great products. And on revenue metrics, Liu said that the company is “fortunate enough to be in a position where, reduced to those numbers, we look very good as a business.”

Assuming that Airtable chose the right investors, a solid financial footing paired with an influx of cash should give the startup room to explore its software creation ambitions. It plans to do so by investing more resources into “Blocks,” which are essentially mini-apps within Airtable, and opening up the platform to “third-party developers and customers.”

It’s an ambition that’s fraught with potential problems. One only need look at the list of poorly maintained Google Doc Add-ons and Twitter’s lackluster handling of over the years to understand the potential perils, and responsibility, of calling yourself a platform. But the use of the buzzword isn’t lost on Liu.

“Not all platforms are created equal. It’s kind of in-vogue to call yourself or something a platform because it sounds more ambitious, more empowering, and more important to do than build a product,” said Liu.

Even without third-party developers, Airtable plans to commit internal resources to its Blocks platform, likely an encouraging sign for developers.

“We’re going to have a full-time team… to go and just build useful blocks on top of our own platform,” said Liu.

To this writer, in many ways, Airtable is attempting to create a new economy of app development built off of its accessible database. It’s a tall order that will require millions, and this is the bull market to raise it in.

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