Biotech Growth Opportunities

Tough pill to swallow as scientist at an early-stage biotech startup: If you don’t make the science work, on time & on budget, the company will die. Here’s a tried & tested framework for dealing with that 👇 Science at early-stage startups is 🧪 Fast-moving 🧪 Ever-changing 🧪 And first and foremost……outcomes-oriented! If you’ve spent your entire career to date in academia, this may feel unsettling at first. Here’s a framework for navigating outcomes-oriented science: 1️⃣ Zoom out. Get clear on the scientific & business outcome the startup needs to get to profitability. Focus on identifying unnecessary assumptions are constraining you - even if it’s an assumption your manager or CEO made! Example: You need a cell-line with particular characteristics to produce antibodies, which you will sell. Assumptions: 🧪We should make this cell line in house (should we make an off-the-shelf purchase instead?) 🧪The antibodies should be produced via cell line (is another system possible?) 2️⃣ Break the problem into its scientific/business parts. Example: What needs to be true about this cell line? It needs to grow quickly, cheaply, scale in some way, and have an optimized ability to produce antibodies. First principles thinking is key here! Biologists can take a lot from the engineering playbook. 3️⃣ Parallelize a few strategies to achieve this outcome. Consider: How can you ensure these strategies fundamentally de-risk each other? How can you try to solve the problem from multiple angles such at least one might yield the necessary outcome on time? Example strategies to parallelize: 🧪Purchase several cell lines which produce antibodies well. 🧪Chose 3 x potential in-house cell lines which are derived from very different sources. Optimize for reduced costs, quicker doubling times, and scale. 🧪Throw a small amount of resources at a long-shot technique which uses a microbial system to produce antibodies 4️⃣ Monitor progress regularly and cull projects as needed. Example: After 1 month, the microbial system is yielding surprisingly good results. 24 hours later, all cell line work is de-prioritized and the system starts again, zoomed in on microbials _________ Personally, I think that the startup model of science is exhilarating - it gets pretty addicting to see how much tangible impact you can make in a matter of months, rather than years!

If I had to give one tip to biotech startups, it would be to use Design of Experiments (DOE). It helps you save time and get more reliable results. I first heard about DOE during my Master’s in Industrial Biotechnology. It was introduced as a way to speed up experimental design. At the time, I was still convinced that optimizing a process meant changing one variable at a time. Temperature, then pH, then nutrients. I had the chance to apply DOE in my first job. That’s when I saw the real difference. The sequential approach was slow, often misleading, and blind to how variables actually interact. With DOE, I could: -Test multiple factors at once -Detect hidden interactions -Build predictive models without running every single experiment. That changes everything, especially in fermentation, where parameters are tightly interconnected. I’ll give you a concrete example. A team was optimizing enzyme production using 3 variables: temperature, nutrient concentration, and agitation speed. Sequential method: 27 experiments.DOE method: 9 well-designed tests. Not only did they save time, but they also discovered a key insight: agitation speed strongly influenced nutrient availability. That single piece of information drove faster, smarter decisions. Obviously, when I founded Cultiply, I made sure DOE would be part of our DNA. It allows us (and our clients) to reduce uncertainty and make solid technical choices from the start.

Biologicals: The Key to Unlocking Next-Level Productivity!! Crop productivity has hit a stagnation point, primarily due to the saturation of chemical fertilizers. Despite increased application, chemical inputs are no longer delivering substantial gains in yield. To break through this ceiling, the next leap in productivity must come from innovative solutions like biologicals. Biologicals, such as nano biofertilizers, biostimulants, and bio-pesticides, present an advanced, sustainable approach to crop nutrition and growth. Unlike chemical fertilizers that often deplete soil health, biologicals work in harmony with the soil ecosystem, boosting nutrient availability, enhancing plant resilience, and improving overall soil fertility. One of the game-changing advantages of biologicals is their efficacy when applied via foliar methods. Nano biofertilizers and biostimulants, delivered directly to plant leaves, can be absorbed more efficiently than synthetic fertilizers applied through the soil. This targeted approach allows plants to access essential nutrients immediately, optimizing growth without the environmental runoff issues common with traditional fertilizers. Moreover, biologicals can be customized to align with different phases of the crop cycle. Whether it's vegetative growth, root zone development, or the reproductive phase, biologicals can be precisely formulated to meet the plant's specific needs at each stage. This level of customization is a major step forward in maximizing the productivity of field crops, ensuring plants get the right support at the right time for optimal growth and yield. As we face the twin challenges of increasing global food demand and preserving environmental sustainability, biologicals are emerging as the critical tool for the future of farming. By adopting these innovative, nature-based solutions, we can push productivity to new heights, sustainably. Now is the time to shift from chemical dependence to biologically powered agriculture.

Beyond fossil feedstock - how biotechnology unlocks resilient, high‑value growth Great to read in this article about the biotechnology industry in India - highlighting how biotechnology is already catalysing circular and bioeconomy outcomes - through bio‑based materials, waste valorisation, renewable energy, and bioremediation. The article showcases how turning agricultural and industrial waste into biofuels, bioplastics, and biofertilisers can cut reliance on fossil fuels and chemical‑heavy processes, while enabling sectors like agriculture, healthcare, and manufacturing to recycle and reuse resources more efficiently. For New Zealand, the interconnections between the bioeconomy and circular economy are clear - targeting resource recovery, ecosystem protection, and resilient communities while producing value added bio‑based products, reduce emissions, and lift economic value. The New Zealand Institute for Bioeconomy Science Limited accelerates this transition: advancing innovation in horticulture, agriculture, aquaculture, forestry, biotechnology and advanced manufacturing - developing new bio‑based technologies and products. We’re already seeing the momentum: ✅ Waste‑to‑resource at scale - Ecogas converts ~75,000 tonnes of food waste into renewable energy and returns nutrients to soils via biofertiliser, demonstrating circularity in action. ✅ Policy‑enabled growth - Government investment in biodiscovery and advanced tech is unlocking new bioproducts and export pipelines - this is where New Zealand's unique biodiversity and biomanufacturing strengths can shine. ✅ Primary industries & industrial biotechnology - From biomass residues to advanced biomaterials and manufacturing - Our ability to sustainably grow biomass can power a low‑carbon, circular bioeconomy. What are we accelerating? ✅ Scale precision fermentation, bioprocessing and synthetic biology to convert diverse side streams into high‑value ingredients and materials. ✅ Deploy data/AI and sensors to optimise biomanufacturing and supply chains, improving efficiency and traceability across sectors. ✅ Embed kaitiakitanga and mātauranga Māori within circular system design to create solutions that are culturally grounded and regenerative. Partner with the Bioeconomy Science Institute to turn world‑leading science into impact - here in New Zealand and around the world. We co‑develop and scale innovation across agriculture, horticulture, forestry, aquaculture, biotechnology and manufacturing - optimising biological resources to deliver food and materials from resilient supply chains while protecting ecosystems from biosecurity threats and climate risk. #Bioeconomy #CircularEconomy #Biotechnology #NewZealand #WasteValorisation #Biofuels #Bioplastics #Biofertilisers #AdvancedMaterials #GreenGrowth https://lnkd.in/eQKByaZr

The biotechs that raised money in 2025 weren't the ones with the best data. I had 445 in-person meetings this year with life science CEOs, CFOs, and investors. The pattern was clear... Investors stopped funding the "best science." They started funding teams most likely to survive: - Regulatory chaos - Program failures - Capital scarcity Here's what separated survival from struggle... 1. They Expanded Capital Geography When $3.8B in NIH grants froze, three of my clients secured funding from European family offices and Asian biotech programs. The move: US capital sources remain selective. European family offices, sovereign funds, and overseas strategic investors are actively deploying. If your only fundraising conversations are domestic, you're ignoring available capital. 2. They Built a Regulatory Buffer A CFO told me their FDA contact's email bounced mid-approval. Three weeks later, it reactivated with no explanation. The FDA's Center for Drug Evaluation and Research lost 385 employees in the first half of 2025, more than triple the prior year. Extended timelines became standard. The move: Budget 18-24 months of runway, not 12. Companies that used delays to strengthen data packages were ready when agencies responded. 3. Community Became Competitive Advantage San Diego's life science ecosystem shares real-time intel on active investors, CRO performance, and which advisors overpromise. Isolated founders scrambled while connected ones had solutions before problems became existential. The move: Your peer network is better due diligence than any consultant. 4. Storytelling Closed Deals Great science alone didn't close deals. Teams that combined data with tight investment narratives, partnership paths, and de-risking milestones dramatically outperformed those who assumed science would speak for itself. The move: Investors need your de-risking roadmap first. Teams that answered up front closed deals while science-only pitches struggled. 5. They Moved Before Risk Compounded A client faced a European trial launch with significant USD/EUR exposure. They hedged early. When the dollar weakened 13% against the euro in 2025, that hedge prevented cost overruns. The move: Lean on specialized expertise early. Model risks and act before problems compound. What's Ahead? Multiple clients are exploring M&A, partnerships, and IPOs. With interest rates declining and capital markets thawing, the window is opening. 2025 rewarded teams that diversified capital, built regulatory buffers, invested in narrative alongside science, and made hard calls early. 2026 is shaping up to be the year of superior execution. Join Me in February If you're a life science founder or CFO preparing for 2026, I'm hosting a happy hour in San Diego on February 4th, limited to biotech operators. Reach out if interested, and I'll add you to the waitlist.

Biotech startups don’t fail because they run out of cash. They fail because they waste it. I’ve spent years watching startups go from “disruptive” to dead in the water....brilliant ideas, brilliant teams….. no product. So here’s the thing: ↳ It’s not about funding. ↳ It’s about focus. ↳ And the things nobody talks about at pitch night. 5 real reasons biotech startups go sideways: 01. Chasing ‘Cool Science’ Over Real Problems  ➔ Too many founders fall in love with the tech, not the impact. A glowing molecule won’t save lives if no one needs it. Before you hit the lab, hit the street. ↳ Talk to hospitals. Talk to patients. Talk to insurers. ↳ Look at companies like Tempus AI and Flatiron Health—they started with the pain points. 02. Regulatory Naivety ➔ The FDA isn’t just a hoop to jump through....it’s the mountain. If you don’t respect it early, you’ll pay for it later. ↳ Partner with ex-regulators before you hit pre-clinical. ↳ Moderna didn’t just move fast—they moved smart. 03. Hiring Academics Who Can’t Scale ➔ We love science. But not every brilliant researcher should run a business. A postdoc with 47 citations isn’t your COO. ↳ Pair them with operators. People who’ve scaled. People who’ve exited. ↳ Think Flagship Pioneering—they build teams, not just tech. 04. Ignoring Manufacturing Hell ➔ You can’t commercialize what you can’t produce. Cell and gene therapies fail not because they don’t work but because they’re impossible to scale affordably. ↳ From day one, ask: how will we build this? ↳ Companies like Resilience are leading here for a reason. 05. Data Silos That Kill Collaboration ➔ Biotech is drowning in Microsoft Excel sheets and custom code. Good luck running trials on spaghetti data. ↳ Enforce FAIR data principles. Build with reproducibility in mind. ↳ Look at Benchling and DNAnexus, data-first platforms enabling real science, not hacks. This carousel isn’t to scare you. It’s to save your runway. Founders: stop chasing the shiny. ↳ Build for the real. Build for the long game. ↳ Because curing disease is hard enough. Let’s not sabotage ourselves in the process. How’s your team handling these 5? Comment below 👇 . P.S. This one’s personal. I’ve worked with scientists, VCs, and founders who had everything but the roadmap. If that’s you, don’t wait. Get help early. Build smarter. 📌Tag someone who needs to see this. ♻️Repost if it resonates.  👉Follow for more unfiltered takes on biotech, brain tech, and scaling what matters. #Neurotech #BrainMind #Innovation #BrainScience #Biotech #Neuroscience #Leadership 

🚨 I analysed all $10M+ biotech funding rounds from the past six months. Here’s the direction we’re heading in 👇 - Hundreds of companies & deals. - Billions raised. - Deal flow still slower than usual - but capital is moving again. 🧬 𝗚𝗲𝗻𝗲 𝗘𝗱𝗶𝘁𝗶𝗻𝗴 𝗶𝘀 𝗯𝗮𝗰𝗸. → Funding is climbing fast. → Investors are moving past CRISPR headlines - toward delivery systems, manufacturability, and non-viral platforms. → This is where the next build-out begins. 💥 𝗔𝗗𝗖𝘀 𝗮𝗻𝗱 𝗕𝗶𝘀𝗽𝗲𝗰𝗶𝗳𝗶𝗰𝘀 𝗮𝗿𝗲 𝗮𝗰𝗰𝗲𝗹𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗮𝗴𝗮𝗶𝗻. → Rounds are big - several $100M+ raises this year - but fewer players. → We’re entering “ADC 2.0”: smarter payloads, bispecific formats, and CDMOs scaling capacity. 🏗️ 𝗠𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗶𝗻𝗴 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 (𝗖𝗗𝗠𝗢 / 𝗖𝗠𝗖) 𝗶𝘀 𝗽𝗶𝗰𝗸𝗶𝗻𝗴 𝘂𝗽 𝘀𝗽𝗲𝗲𝗱. → Investors are backing enablers - not just therapies. → The next capacity race has already started. 🧫 𝗖𝗲𝗹𝗹 𝗧𝗵𝗲𝗿𝗮𝗽𝘆 𝗶𝘀 𝗰𝗼𝗼𝗹𝗶𝗻𝗴. → Fewer rounds. Smaller checks. Consolidation everywhere. → Leadership turnover usually follows - not expansion. 🧠 𝗔𝗜-𝗗𝗿𝘂𝗴 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 𝗵𝗮𝘀 𝗹𝗼𝘀𝘁 𝗺𝗼𝗺𝗲𝗻𝘁𝘂𝗺. → The hype hasn’t vanished, but focus has shifted. → The winners will be those who embed AI in discovery - not make it the story. 📈 𝗠𝘆 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗼𝗻: ➡️ The next phase of biotech growth will be built around Gene Editing + Delivery, ADC 2.0, and Manufacturing Scale-Up - the platforms that make advanced therapies possible at scale. 👥 𝗪𝗵𝗮𝘁 𝗱𝗼𝗲𝘀 𝘁𝗵𝗶𝘀 𝗺𝗲𝗮𝗻 𝗳𝗼𝗿 𝘁𝗮𝗹𝗲𝗻𝘁? → Hiring patterns are already shifting. → The companies building infrastructure and integration capability will win. Expect rising demand for: • CMC and Manufacturing Operations leaders • BD heads in ADC and delivery technology • Cross-functional executives who can link science, scale, and strategy These hires are already coming up in our searches, and I doubt it'll change any time soon. Need some help hiring in these areas? Let me know - always happy to chat. #Biotech #LifeSciences #VentureCapital #GeneEditing #ADCs #CDMO #ExecutiveSearch

Platform biotechs may be less in vogue, but there’s still a compelling path forward. I discussed what it takes to build a successful platform company in 2024 with BioPharma Dive highlighting three key considerations. #1: Think about the lead indication from day one. The days of building a platform first and hoping it finds a target are gone. Build the platform around the target, not the other way around. #2: The popular strategy—starting with a lower-risk, lower-value target to prove out the platform before pursuing a higher-value one—is no longer as viable as it was. You must begin with the high-value target right out of the gate. #3: You only get one “true-believer” round. After that, new investors will judge you solely on the value of the assets you’ve generated. Despite challenging markets, the quality of platform biotechs I'm seeing is higher than ever. Excited about what this generation can achieve. Thanks to BioPharma Dive and Gwendolyn Wu for the opportunity to share these thoughts

MedTech’s Next Frontier: Regenerative Biomaterials Regenerative medicine isn’t just for biotech anymore—MedTech companies are making bold moves on their own, leveraging proven biomaterials (allograft, xenograft, resorbable synthetics, etc.) as the foundation for tissue repair, healing, and even drug delivery. Why now? As we all know, there is a plethora of biomaterial products used today across MedTech specialties (see image, not exhaustive, but you get the point!). That said, trends are aligning that will accelerate the investment in next-generation, regenerative biomaterials: * Biomaterials have evolved from passive scaffolds to active platforms enabling localized therapy and regeneration * Technology and capabilities are expanding to enable novel combination product development (multi-biomaterial, biomaterial + drug) * Regulatory and access, while still challenging, is workable and several examples have been able to achieve success (e.g., Vericel® Corporation’s MACI) * The need for innovation is increasing as traditional implants become ubiquitous and OEMs search for novel solutions to address critical patient needs Emerging Categories and Trends to Watch: * Combination (Multi-Biomaterial) Products: Ability to deliver custom properties to specific use cases benefiting from the strengths of each biomaterial type. Examples include: Vericel® Corporation’s MACI and CONMED Corporation’s BioBrace but we expect more products to come to market imminently * Biomaterial-Drug Platforms: Localized delivery of antibiotics, growth factors, and anti-inflammatory agents via regenerative scaffolds. Examples include: Boston Scientific's (Elutia's) EluPro, Medtronic’s TYRX and (IntersectENT's) PROPEL, Cerapedics Inc.’s PearlMatrix, a number of drug eluting stents, and other, allogeneic therapies like Isto Biologics’s ProteiOS and DiscGenics * 3D Bioprinting & Nanotechnology: Patient-specific implants, custom bioprinting, and tissue models for complex reconstructions. Nano-engineered surfaces are also improving osseointegration and fusion rates, especially in spine and trauma. Examples include: BRINTER, Curiteva, Inc.’s INSPIRE, restor3d's r3id, and Carlsmed’s aprevo * Adaptive Biomaterials: Responsive to pH, temperature, or biological signals for controlled release and adaptive healing. Examples include: inSoma Bio * CDMO Partnerships: MedTech is leveraging specialized manufacturing from key CDMOs who have invested in next-generation capabilities and biomaterials to scale regenerative portfolios quickly. Examples include: Evergen and Regenity Biosciences At Health Advances, we have been busy across all biomaterial end-markets and innovations and are excited to help guide our clients on these exciting markets!

AI-bio companies are often mis-sized. In consumer AI, the strategy is often to raise large, hire fast, and build big, with the bottleneck being engineering scale and product-market fit. It doesn't work for biology, where the real bottlenecks are judgment, which experiments to run, which signals to chase, which to ignore. There is a newer model in biotech: Keep the core team small and senior. Outsource the heavy, capital-intensive work, such as wet lab, to contract research organizations (CROs) you can turn on and off. Own the judgment in-house; rent the execution. The fixed cost structure stays low, which makes the company hard to kill: you don't have to raise large amounts or burn fast to survive, so you can hold a position for years and wait for the experiment that matters. These companies look more like research labs than Series B startups. The constraint is senior judgment, not headcount — and a low burn rate is what buys you the time to apply it. This isn't a knock on the larger players. Recursion, Isomorphic, Insitro and others are building the opposite way — massive automated labs, brute-force scale — and some of them will work. It's an observation about variance. The smaller, more deliberate companies tend to produce surprising results because they have the time and seniority to recognize a signal that a less experienced team would dismiss. You can already see it in the programs, if not yet in the approvals. Insilico's rentosertib — a first-in-class molecule where both the target and the compound came out of generative AI — reached positive Phase IIa by nominating a candidate after screening 78 molecules, not thousands, in 18 months at a fraction of the usual cost. Forty years in AI taught me the same lesson the last two decades of drug discovery teach: most consequential drugs came out of small teams with strong PIs. In biology, AI doesn't remove the need for judgment. It raises the premium on it.