What you need to know: 

• Animal health is seeing rising demand and early-stage startups are building novel products targeting the space, including AI-based solutions.
• Focus areas for emerging trends include: Diagnostic platforms for vets, advanced therapies, methane-reducing solutions, AI-driven diagnostics & monitoring, and disease prevention & treatment.

Animal health — which includes companion and livestock animals — is steadily growing as a topic of interest among executives.

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Essential resources to understand the future of healthcare:

• • The generative AI in healthcare market map — These tech companies are bringing generative AI into medical research and clinical settings.
  • Pharma AI Readiness Index: Who’s best-positioned for the AI boom? — Assess how prepared top pharmaceutical companies are to adopt and respond to rapidly evolving AI technologies.
  • 6 digital health markets gaining momentum in 2024 — We analyzed early-stage investment trends to uncover which digital health markets — from telepsychiatry to virtual & hybrid women’s healthcare — are quickly evolving and how.
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  • The Digital Health 50 — Here are the world’s most promising digital health startups.
  • Big Tech in Healthcare — How Amazon, Google, Microsoft, & Nvidia are looking to transform drug R&D, primary care, and more.
  • State of Digital Health Q2’24 Report — Funding in digital health drops, but larger check sizes and an uptick in exits highlight bright spots for the industry in Q2’24.
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  • Longevity tech market map — 64 promising startups across 12 categories aiming to expand lifespans, from human cryopreservation to cellular reprogramming.
  • Digital Health AI M&A — Every second acquisition in 2024 has been an AI company; here’s where we’re seeing the most activity.
  • 20 tech trends to watch closely in 2024 — The technology trends that will transform industries as generative AI takes center stage, including several directly impacting healthcare.

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In 2024 so far, a16z has backed more than 20 AI startups working within disruptive categories. For example, this year, it has invested in several AI-driven copilots and agents designed to automate key workflows in big industries like healthcare and finance. It has also turned its attention to multimedia generation startups expediting the creation of a wide variety of content, from images to videos to audio.

While championing AI’s advancement, the firm also acknowledges associated risks — its founders are proponents of open-source models, arguing that their transparency and accessibility will help ensure that AI is developed in a secure and ethical way. So far this year, the two largest a16z-backed AI deals have gone to open-source large language model (LLM) developers xAI and Mistral AI.

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As a result, a range of technologies have emerged to address issues across the entire trial lifecycle. These use AI, data analytics, and digital platforms to streamline processes, improve data quality, and boost patient engagement — all with the aim of driving down trial times and costs while increasing success rates.

This market map identifies 96 vendors in 14 categories reshaping clinical trials. This tech ecosystem offers sponsors and research organizations opportunities to conduct more efficient, patient-centric trials that also meet regulatory requirements.

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This acquisition follows Commure’s Oct 2023 acquisition of another AI-driven provider workflow solution Athelas — which offers revenue cycle management (RCM) and automated documentation services — further bolstering its AI arsenal.

These deals reflect a key trend in healthcare M&A: AI is all the rage. 

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The impact on the pharma industry has been substantial, with Ozempic’s producer, Novo Nordisk, seeing a 36% rise in sales in 2023 driven by the accelerated adoption of its GLP-1 products. D2C pharmacies like Hims are also entering the space, offering their own GLP-1 drugs at a fraction of the cost to patients. 

The rapid growth in prescriptions for these appetite-curbing drugs has drawn wide-spread attention from corporates across industries.  

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The pharma giant is partnering with companies to speed up drug discovery using AI. These efforts extend across its core R&D focus areas, including immunology and oncology.

The company is also leveraging partnerships and investments to enhance clinical trials and bring its 75+ clinical-stage projects to market more quickly. For example, Sanofi Ventures led a Series B round for Nucleai, which uses AI to help drugmakers understand how patients will respond to their drugs and, as a result, select the most suitable patients for clinical trials.

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These leaders are harnessing their existing offerings — in areas like cloud computing, AI, and hardware — to service healthcare providers and pharmaceutical companies.

While big tech players are competing with each other in this landscape, they are also carving out distinct strategies: 

• Amazon is going deeper into primary and specialized care.
• Google is amassing troves of health data, which could play a role in its biotech bets. 
• Microsoft is equipping healthcare organizations with AI tools to improve clinical research, drug R&D, and care delivery.
• Nvidia’s long-standing hardware dominance positions it to play a major role in the future of smart hospitals. 

This report uses CB Insights datasets like investments, acquisitions, business relationships, patents, buyer interviews, company scouting reports, and more. Learn more about our data here.

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The industry is built around encoding information in quantum entities called “qubits” — which have a probability of being either 1 or 0, as opposed to traditional bits that can only be one or the other — to open up new computational approaches and ways of handling data that are not possible on conventional devices.

For example, quantum computing could allow entirely new algorithms that are much more efficient at some key tasks — like complex optimization problems, sorting through large datasets, and running simulations. Though the tech is not yet mature, companies are already working to apply quantum computing to commercial applications like drug discovery, finance, materials discovery, and logistics. Investors are excited — startups in the space saw equity funding surge to $1.3B in 2023, a rare bright spot for venture last year. As quantum computers become more capable in the coming years, expect commercial interest to rise quickly.

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Salesforce CEO Marc Benioff called AI “the single most important moment in the history of the technology industry” in the company’s most recent earnings call. JPMorgan CEO Jamie Dimon said, in his April 2024 letter, “we are completely convinced the consequences [of AI] will be extraordinary.” 

Others are hyper-focused on AI’s potential to drive new efficiencies and product development. Big pharma companies are pushing ahead with AI-powered drug discovery collaborations, with the goal of accelerating drug development timelines. Payments giants, meanwhile, are leveraging AI to fight back against a wave of fraud.  

Much of the hype around recent advances has yet to translate to revenue. No AI-discovered drug has been approved yet for sale (though Insilico Medicine brought the first drug fully generated by AI into human trials in 2023), and Salesforce acknowledged its latest AI push would not have a material impact on its revenue this year. 

But the promise of future opportunities — and the perceived risk of inaction — is driving leaders to make moves now that could eventually reshape some of the world’s biggest industries. Our 70-slide report surveys the AI strategies of the following companies:

• Financial services & insurance: JPMorgan, Visa, Mastercard, UnitedHealth Group
• Enterprise tech: Oracle, Salesforce
• Pharma: Eli Lilly, Novo Nordisk, Johnson & Johnson
• Industrials: Toyota, Siemens

Using the CB Insights technology intelligence platform, we analyzed signals like investment & partnership activity, executive chatter in earnings transcripts, patents, and more to understand their efforts. Download the full report to see them all. 

Largest companies based on market cap (as of 4/15/2024). Our analysis excludes big tech, semiconductor developers, and state-owned companies.

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It’s tackling the issue on all fronts, from investing in AI-enabled care models via Google Ventures, to forging partnerships through its Google Cloud division, to launching new products that tailor generative AI to healthcare use cases.

These moves seek not only to address the challenges facing the sector, but also to strategically differentiate Google from big tech peers like Nvidia, Microsoft, and Amazon — all of whom are making concerted efforts to integrate AI into healthcare.

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The tech giant found a major entry point into healthcare workflows when it acquired Nuance for $19.7B in 2022. It followed up on this by expanding its existing relationship with leading EHR vendor Epic to introduce generative AI across clinical workflows, with the aim of improving provider efficiency and mitigating staffing shortages.

Microsoft’s recent relationships also point to an increasing focus on developing and deploying generative AI in the pharmaceutical industry. The tech behemoth is partnering with and investing in startups in drug development, where early applications of generative AI have seen especially strong investor and commercial traction.

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To reach that goal, the pharma giant is investing internally — it has 178 projects in the pipeline and spent nearly $11B on R&D last year, up 12% from 2022 — as well as looking to emerging technologies that can help it fire on all cylinders.

AstraZeneca has been strategically partnering with companies offering AI drug discovery, diagnostics, and real-world data to help offset some of the cost of drug development and speed up the process. For example, it signed a $247M deal with Absci in December 2023 to develop generative AI-designed antibody therapies for cancer.

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Tech providers are racing to develop simulations — which can replicate real-world scenarios in clinical trials — that can predict drug interactions, patient responses, and potential side effects. 

Below, we’ll highlight a few areas where AI-powered simulations are being used to enhance clinical trials and research across:

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Pharma giant Bristol Myers Squibb (BMS) has done three $4B+ acquisitions since October. Beyond M&A, the company has been active on the partnership and investment front.

We discuss its activity — and the pharma sector more broadly — below.

M&A ACTIVITY

Since October, BMS has acquired 3 companies:

• Mirati Therapeutics ($5.8B) — cancer drug developer
• Karuna Therapeutics ($14B) — psychiatric and neurological drug developer
• RayzeBio ($4.1B) — radioparmaceutical cancer drug developer

LICENSING ACTIVITY

In addition to M&A, BMS has been actively striking partnership & licensing deals with other biopharma companies.

You can see 4 licensing deals it’s struck just since October as well courtesy of CB Insights commercial transaction data.

INVESTMENT ACTIVITY

And finally, the pharma giant remained an active corporate venture capital investor in 2023.

Its deal activity held up pretty well in an otherwise down year for venture.

Within its venture investments, BMS is deploying money into new companies and not just following on in existing investments as the graph below illustrates.

BIG PHARMA ACQUISITIONS

Pharma giants are sitting on a lot of cash, and with some having drug pipelines that need replenishment, 2024 should be a big year for M&A activity in the pharma space overall. 

2023 already marked a major upswing in activity.

Pfizer completed its $43B acquisition of Seagen in December. Meanwhile, AbbVie announced back-to-back acquisitions worth nearly $19B combined in Q4.

Heading into 2024, BMS has likely put everyone else’s corp dev and licensing/R&D teams on alert that it’s go time.

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On the drug R&D front, pharma players are using the tech to design new drugs in a fraction of the time. For instance, Insilico Medicine has brought an AI-generated drug for idiopathic pulmonary fibrosis to Phase II human clinical trials — in about half the time it would take without AI. Startups here saw a flurry of exit activity in 2023 as incumbents race to get involved.

Meanwhile, in the hospital setting, genAI is helping summarize complex doctor-patient interactions, make EHR entries more precise, and enhance diagnostic imaging. Cloud giants like Microsoft and Amazon have announced clinical documentation services that allow providers to automatically create medical notes, while EHR leader Epic has partnered with Microsoft to integrate genAI tools into its EHR system. 

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Companies helping women better deal with menopause symptoms raised $230M in equity funding in 2023, up 22% from 2022. This accounted for over a third of all women’s health funding — which plummeted from $1.4B to $648M over the same period. 

Investors see clear growth potential for menopause care — driven by unmet demand for access to medical services specifically for menopause symptoms and by employers becoming more willing to pay for menopause care services as part of employee benefits packages.

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Studies have shown that new drug discovery and development can cost between $1B and $2B on average. However, an APSB study showed that this costly process only results in a marketable drug about 10% of the time when using traditional methods. In the clinical trial space, failed trials cost the industry more than $45B per year.

As a result, technology that can improve the efficiency and efficacy of pharmaceutical research can yield massive savings. Generative AI, for example, can be used to enhance various components of the trial process, in some cases allowing potential issue areas to be identified before arising in a live trial.

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Healthcare isn’t an entirely new sector for Nvidia. It invested in healthcare-focused computer vision startup Zebra Medical Vision, for instance, back in 2017.

In the past few years, however, its investments and partnerships have coalesced into a clear strategy, as the chipmaker builds on its work in advanced computing to lay the foundation for next-gen AI applications in health IT. For instance, it has redoubled efforts in areas like edge computing, which makes it easier to deploy AI in care settings where broadband internet connectivity is limited or nonexistent.

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Over the last few years, Bayer has forged business relationships with other organizations to help prevent, diagnose, alleviate, and cure diseases.

One goal unifying Bayer’s activity is that it is looking to expand beyond traditional drug discovery and development. To do so, the pharma giant is rapidly tapping into a variety of emerging technologies, including digital therapeutics, real-world data, and artificial intelligence.

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Pharma players are already using AI to understand viral structures, identify small molecule drug candidates, and design novel proteins. They’re also embracing the technology as a way to streamline clinical trials, from patient recruitment to protocol design.

The space has seen a flurry of investment activity and consolidation this year. Biopharma player Recursion, for instance, acquired 2 startups — Cyclica and Valence — to boost its generative AI capabilities, while XtalPi, which applies AI to small molecule drug discovery, announced a partnership with Merck and a $250M deal with Eli Lilly.

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To fight this disease, tech companies are supporting patients, providers, and pharma players by developing tools to improve cancer care, diagnosis, and drug discovery. 

Solutions like liquid biopsy screening are less invasive, faster, and more cost-effective than traditional biopsies, while cell behavior simulations can model tumor behavior to speed up drug R&D.

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In May, Eli Lilly signed a $250M collaboration with XtalPi, the top-funded startup in AI drug discovery & design. Mentions of AI surged in AstraZeneca’s Q1’23 earnings call. And Sanofi announced its ambition to be “the first pharma company powered by artificial intelligence at scale” in a press release in June.

But which ones are best equipped to take advantage of the technology?

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Tech vendors are helping pharma companies and other healthcare organizations address roadblocks throughout the clinical trial process. For instance, EHR-based patient recruitment solutions help improve adherence to enrollment deadlines, while decentralized clinical trials can increase patient accessibility and diversity.

In the market map below, we identify 63 vendors digitizing clinical trials across 10 different categories.

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RWD — an umbrella term for patient data mined from health records, insurance claims, clinical registries, genomic databases, and surveys of patient-reported outcomes — was initially used to collect evidence about a drug‘s post-market safety.

Today, these datasets are being used to match patients to the right trials, design study protocols, create simulated control arms in clinical trials, and identify promising drug targets.   

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