cc: Life Science Podcast

• Life Science Sales - Old Way vs New Way

  Recently, I’ve enjoyed interviewing people I have never spoken to before. Harrison Waid, the co-founder of Succession, is one of those. Shout out to Teddy Lin for connecting us. I took this as an opportunity to learn about Harrison and his business as well as a personal challenge to interview someone “cold”. OK, I did some research, so maybe “room temperature”.First of course, I needed him to explain Succession, co-founded with Nick Clare (who I hope to have on another time). They noticed life science companies struggling to translate great technology into successful market entry and sales growth. Succession was founded to address this, offering specialized services exclusively for life science sales teams – everything from lead generation and sales training to recruitment and optimizing internal systems like CRMs with automation and AI. Harrison called it a "vertical service company" for life science sales.The idea for it wasn't a sudden flash of insight but more of a "slow burn." While at Synthego and after moving to the UK, he initially thought about general consulting. He quickly found that clients wanted concrete outcomes, not just advice. The real traction came when they packaged their expertise into specific, deliverable-focused services – that’s when things really took off.I’m always interested in people who come from other backgrounds outside of life science. He made his start was in software sales. A friend brought him into Synthego, a CRISPR company, initially for consulting. At that point, his knowledge of biology was that "the mitochondria is the powerhouse of the cell." But he was excited by the potential of the technology. He immersed himself in learning the science and business of biotech, leveraging online resources and learning from his colleagues. Once again, curiosity = superpower! Asking "dumb questions" is an underrated skill. Those outside perspectives can challenge assumptions and benefit both the business and the individual willing to learn.I'd prepped some questions, but the morning of our interview, I stumbled upon a recent LinkedIn post Harrison made contrasting "old" and "new" ways in biotech sales. I saw some insightful comments from people we both respect, like Owen Swift. I knew this would be worth digging into.Harrison framed the "new way" around leveraging technology to move beyond inefficient models like (old way) simply scaling headcount. I picked a few points from his post for discussion:Small, High-Output Teams + RevOps/Content/Automation: He explained how technology now allows high-performing reps to be supported by robust systems (managed by Revenue Operations) that automate much of the prospecting and research previously done by separate inside sales roles. This frees up skilled sellers to focus on closing.AI for Intent & Sequencing: We discussed how AI can go beyond basic alerts to analyze market signals, identify key opportunities, score leads, and even assist with outreach, providing reps with powerful, timely intelligence.Content & Personal Brand for Demand Gen: I strongly agree with this one. There is a compelling case for reps building their personal brands on platforms like LinkedIn. He argued, quite correctly in my view, that authentic content from individuals resonates far more than corporate posts and that companies restricting this are missing a huge opportunity.Video Outreach: I shared my own recent positive experience with video messaging, having secured a meeting from one just last week. Harrison pointed out how video cuts through the noise, humanizes interactions, and is effective for both prospecting and follow-ups. We agreed authenticity is more important than perfection.The Best Reps Get the Best Opportunities: This one may be controversial, as it goes against the idea of pure "fairness" in lead distribution. He would argue that for maximizing company revenue, it makes sense to give the highest potential leads to the reps most likely to convert them. He acknowledged territory assignments are inherently unfair anyway and suggested lower performers could develop on less critical leads. This leads to discussions about efficiency, long-term strategy, and even healthy team turnover.Compensation plans inevitably drive behavior and can always be gamed, so no system is perfect. It comes down to your goal and again, long-term strategy. As someone who hasn’t formally been in sales, I can see the attraction to developing skills on low risk opportunities.If these ideas got you thinking, you might check out the SalesDNA Podcast, Hosted by Harrison and Nick. These cold conversations have been a blast and educational for me beyond the content. I have more lined up. If you aren’t subscribed, now might be a good time…Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.BTW, I hope you’ll consider joining me here: This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cclifescience.substack.com

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  30:35
• Process Optimization for Alternative Proteins Using Adaptive Learning

  Large language models (LLMs) seem to dominate the discussions, at least in my world lately. In this episode and the next, we’re diving into AI on a different scale. In this episode, I spoke with Josh Hinckley, co-founder and CEO of Bioqore. AI is being applied to the way we make things — in this case, food. Josh’s background in materials chemistry has led him to focus on process optimization for alternative proteins, where the challenges in the market are high: you have to make large quantities efficiently, the price point has to be realistic for consumers and on top of all that, the end product has to meet all your sensory requirements. A fancy way of saying it has to smell, taste and feel right.When you're making pharmaceuticals, small yields are fine because the value per milligram gram is high. But for food, you need much larger quantities. People aren’t going to pay $100 for a gallon of milk. So alternative food companies are under pressure to optimize production at a scale biotech typically doesn't deal with.The example he gave was alternative milk. It’s real milk, but produced without cows. It looks, tastes, and behaves exactly like traditional milk but doesn’t require pasteurization. But moving from liquid milk to structured products like meat is a much bigger challenge, because the texture and mouthfeel matter just as much as the composition. Food isn’t just chemistry, there is an emotional component to eating (memories, adventure…).That’s where Bioqore’s AI platform, Voyager, comes in. In contrast to traditional design of experiments (DOE) methods that can be rigid, and sometimes inefficient, Voyager uses active learning, a machine learning approach that continuously refines its model based on outcomes. Instead of running 20 experiments at every stage, you might only need five targeted ones to find your optimal process. It's smarter, faster, and cheaper.Not subscribed? Let’s fix that. No spam, just good content wherever I find it.Josh broke down Voyager’s process into three stages: sampling, exploration, and exploitation. First, it samples combinations of variables broadly to get a feel for the landscape. Then it explores areas where the outputs look most promising more deeply. Finally, once the model understands the system, it exploits that knowledge to hone in on the ideal process. What stood out to me was how machine learning is enabling discoveries humans would likely dismiss. Biology often behaves in unpredictable ways. Human beings are biased by our own limited experience and expectations or mental models of how things should work. Machines don’t suffer from those attachments. They can explore n-dimensional spaces we can’t even visualize and show us possibilities we wouldn’t have believed without the data in front of us. AI is allowing us to see things where we never would have looked.Josh and his team are close to a major leap forward: they’re finalizing investment rounds to support not only their food optimization platform but also rapid therapeutic development, including more efficient insulin production. In just six weeks since we first spoke, Bioqore’s trajectory has accelerated dramatically.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cclifescience.substack.com

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  21:02
• The Longer, Short Way to Sales Success

  When I invited Max Gilbert on the podcast, I suspected the conversation might go beyond sales tactics. Max is the founder of Tiferet Consulting, but he’s also a sourdough baker, amateur rabbi, armchair philosopher, and like me, a pretty bad golfer. Our conversation covered everything from startup struggles to spiritual identity and the joys of sourdough. Helping Scientists Become SalespeopleMax works with founders selling into biotech or pharma that want to make sure their first sales hire works out. Spoiler: He has seen it go bad which gave him the idea.One can imagine a founder with a science or engineering background thinking, “I’m not a sales person. I need to offload this to someone who can make calls, pound the pavement and hit a number.” The early-stage sales role is fundamentally different. It’s about iteration and discovery, not just execution. So instead of trying to fit a traditional salesperson into a startup that was still finding its feet, Max found more success coaching fermentation scientists and bioprocess engineers to do the selling. They could speak their customers’ language and earn trust through technical credibility. Max helps them build the confidence and process to go with it.Here is some good, if scary, news for those folks. As a scientist, you have skills that are useful in sales. Once again, your curiosity is a superpower. Sales, according to Max, is asking questions, looking at a problem from a lot of angles and figuring out how it might be solved. The challenge, as I see it, is that having developed a product or service, a founder might feel they have the answer in hand and they can’t wait to tell everyone who might be interested. They end up filling the silence with features and benefits.Sales as a Scientific ProcessMaybe a better approach is to think about your product or service as a hypothesis. And every sales call tests that hypothesis by asking more questions of the prospect about what they do. What’s this person struggling with? How do they think about their problems? When you listen that way, your product becomes a natural extension of the conversation. Then you can frame your product as a possible solution and let the prospect decide if they want to have another call to talk about it some more.The process becomes a collaborative journey. Are we solving the right problem? Do we even understand the problem? Can we help? And if not, Max coaches his clients to say so and maybe even refer that prospect to someone who can.Why Scientists Should Own the Sales Process EarlyOn top of all that, for the first few sales, only the founder can have the context to ask all the right questions as well as see how the answers might help refine the product or its positioning.We like to say sales is about relationships, but that can mislead people. It’s not about charm or charisma. For early-stage companies, it’s about using structured conversations to gather data and test hypotheses. Max frames the process like an experiment: design, build, test, learn. When you stop seeing sales as persuasion and start seeing it as discovery and iteration, it becomes a lot more accessible, especially if you’ve been trained to think that way already.Not subscribed? Let’s fix that, shall we? Subscribe for free to receive new posts by email. (No spam. I promise.)Sales is a rollercoaster. Some calls go nowhere. Some start off promising and then you get ghosted. Founders have to keep showing up with curiosity and resilience even when they don’t feel like it. That’s where Max’s coaching comes in. (There is a theme here.)Max’s secret sauce is that he lived the resistance. Like many, he didn’t start out wanting to be a salesperson. In fact, when a mentor suggested he lead sales, his first reaction was visceral rejection. (I laughed out loud as Max mimicked throwing up.) But going through that discomfort gave him a blueprint for coaching others through it. It’s the classic hero’s journey.He told me his coaching isn’t about copying someone else’s process. It’s about helping each founder build their own. Picking the right structure, sticking to it, and having the mindset to carry it through especially when motivation disappears. More on that in a minute.Coaching the Whole PersonI asked Max about this quote on his website: “When we ground ourselves in the identity that transcends our own contradictions, we’re tapping into our authentic self.”Max named his consulting business Tiferet, concept of harmonizing seemingly opposite forces. In a sales context, that means acknowledging both the part of you that wants to help someone and the part of you that needs to hit a number. Instead of shutting one side down, you bring both to the table and accept the tension.Disconnecting from the emotional side of selling and getting comfortable between the extremes is helpful and projects confidence.Avoiding the Trap of the Shorter, Longer WayWe wrapped up with a story Max told from the Talmud about two roads: the short, longer way (full of obstacles and distractions like LinkedIn cheat sheets), and the longer, short way that actually gets you to your destination. TL;DR: You can’t hack your way to real progress. Shortcuts are tempting but costly. Where does success come from? Thoughtful, slow work. Daily practice. Making the process your own. About That Bread…Before we finished, we had to talk about sourdough. Max spends 10 hours a week baking bread. He grinds his own flour and employs some complicated fermentation processes (might be another episode), and thinks of bread as something primal and sustaining. Max’s plan: feed the world with his bread and his wisdom when AI takes all our jobs. Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website.I hope you’ll consider joining me here: This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cclifescience.substack.com

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  35:32
• Can AI Improve Success in Drug Development?

  I had the chance to speak with Petrina Kamiya, Global Head of AI Platforms and VP at Insilico Medicine, as well as President of Insilico Medicine Canada. Insilico Medicine is what Petrina calls a “tech bio”—developing both AI platforms and therapeutic assets, with a flexible model licensing both. Their pharma.ai platform was created to address challenges in drug discovery all the way from target identification to the clinic. In just a few years, they've gone from having two core products to a suite of about 12, all built with a heavy emphasis on validation.When I think about AI in drug development, I think about all the failures in clinical trials. I’ve always wondered: are the molecules themselves to blame, or is the reason for so many failures rooted in the aspects that surround their testing—like patient selection, procedures, or trial design? Petrina confirmed that the two biggest reasons for failure are safety and efficacy. Many failures are turn out to be preclinical issues—either the wrong target was selected, or the molecule causes unintended side effects. AI and machine learning are being used to better predict both, by identifying high-confidence disease targets and designing safer molecules.But predicting toxicity is still a major challenge. There are models at every stage—from in silico predictions to in vitro and animal models—but each layer adds complexity, and good data to train AI models is notoriously hard to come by. A lot of data around failed molecules never makes it into the public domain because it’s proprietary. That means valuable insights about toxicity are often lost, though some substructures known to be problematic are at least captured in public databases. I realize that companies need a return on their investment and even failure data has competitive value. But you have to wonder how much money is wasted chasing dead ends that could have been avoided.The other question I always have is about the mechanics of drug binding. Most approaches focus on the active site—the orthosteric site—where the protein normally interacts with its natural ligand. I asked about the possibility of other strategies like allosteric binding (where a drug binds somewhere else on the protein to inhibit function). Petrina validated that idea along with degraders, which are molecules designed to bring a protein into contact with the cellular machinery that destroys it. These newer modalities, including molecular glues, offer ways to selectively disable problem proteins without relying on traditional binding.Nothing is straightforward. Allosteric sites can offer greater selectivity, which could reduce toxicity. But finding those sites is incredibly difficult because proteins are dynamic and mobile. It’s not just about structure; it’s about motion within the protein itself and context.The body’s backup systems—redundant pathways, mutations, and rescue mechanisms—can undermine even well-designed drugs. This is especially relevant in oncology. Proteins like KRAS have so many variants that it’s not enough to design one effective inhibitor—you often need a panel of drugs to address different mutations. Petrina noted that the human body has many fallback mechanisms, which makes targeting disease pathways more difficult but also explains why drugs that seem perfect in vitro don’t always deliver in the clinic.Not subscribed? Let’s fix that. No spam, just good content wherever I find it.Getting back to clinical trials, AI is mostly being applied operationally right now—to optimize patient selection, identify clinical sites with the right patient profiles, and monitor for trial reporting issues. The big advantage is in stratifying patients to improve the signal-to-noise ratio. As Petrina noted, sometimes a drug works for a subset of patients, but that signal is lost in the broader trial data. That resonated with my previous interview with Kurt Mussina who used AI to identify ideal site locations based on logistics and patient demographics—a very practical, high-impact use of the technology.What if we could recover some therapies that have previously failed because it wasn’t tested on the right people? AI could help salvage and reposition those compounds by uncovering hidden signals in the data. You have to believe that improvements in AI will find a few lost nuggets—digging back through data with better tools to find value that’s already there.Developing therapies aren’t the only application for new molecule discovery. Insilico is also working with companies in the herbicide space, and as Petrina explained, discovering herbicides isn’t all that different from designing drugs for people. You still need target specificity, safety, and cost-efficiency—but at an even greater scale of production. If people or animals are exposed, or if the herbicide lingers in the environment, it has to meet a high safety bar.The unique challenge here is complexity and scale. It comes down to economics. We may spare no expense to extend a human life with doses in the milligram range. In agriculture, you’re looking for a simple compound that is cheap, can be produced in massive quantities, and can be stored in almost any conditions. It’s a new set of constraints.AI in discovery isn’t about magic. It’s about building better foundations—more accurate models, more validated data, and more thoughtful decision-making—to improve every step from discovery to clinical success.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cclifescience.substack.com

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  31:14
• Relational Resilience: Navigating Conflict vs. Resolving It

  I’ve never been great at conflict. Like a lot of people, I’ve leaned toward avoiding it—especially in the workplace. But I know that’s not a useful strategy in the long run, which is why I was excited to talk with Deb Nathan, a conflict navigation coach, on Life Science Marketing Radio.Right off the bat, Deb drew a distinction between conflict resolution and conflict navigation. Resolution implies there’s a clear “winner” and “loser” or at least a compromise everyone can agree on—but let’s be honest, that’s not always possible. Navigation, on the other hand, is about figuring out how to work with each other even when we disagree. It’s about forward momentum, not just agreement.Deb reminded me (and all of us, really) that conflict isn’t inherently bad. In fact, it’s often the spark for meaningful change—personally and organizationally. The issue isn’t the conflict itself but how we choose to engage with it.What Is Relational Resilience?Deb introduced a concept I hadn’t considered before: relational resilience. I’m used to hearing resilience in terms of the individual—bounce back, stay strong, push through. But relational resilience is about how teams manage conflict together. It’s rooted in the idea that we’re stronger and more creative when we work through challenges collaboratively rather than individually.She outlined several components that make up relational resilience:* Relational flexibility – being open to hearing and holding multiple perspectives, including conflicting ideas inside your own head.* Relational confidence – allowing yourself to be vulnerable, which is only possible if the team environment supports that.* Mutual empowerment – shifting from "self-empowerment" to a model where team members lift each other up.* Creativity and imagination – thinking beyond current possibilities and co-creating new solutions.* Appreciating complexity – resisting the urge to simplify when a nuanced approach is more useful. (This is probably my favorite.)* Tensionality – the ability to stay engaged with someone else’s perspective while still holding your own.* Comfort with uncertainty – resisting the rush to answers when patience could produce better outcomes.* Reasonable hope – a grounded belief that things can improve with effort, even if it’s not easy.It’s a powerful framework, and it aligns with how I like to think: long-term, with an eye on creating something that lasts.Vulnerability as a Leadership SkillWhen we got into the topic of vulnerability, Deb made a point I’ve seen play out in real life. The best managers I’ve had were the ones who gave me space to try things—even when those things didn’t work out. They made it safe to take risks. And when something failed it was a learning experience, not a career-ending mistake.Deb emphasized that leaders don’t need to have all the answers or even agree with every idea. What they do need is to create an environment where people feel safe to experiment and speak up. That’s where vulnerability comes in—not just for individuals, but systemically. Managers who can admit uncertainty, invite multiple viewpoints, and reflect on outcomes together build healthier, more resilient teams.Curiosity Is a SuperpowerIf you’ve listened to more than a few episodes of this podcast, you know I’m a big fan of curiosity. So is Deb. She described curiosity as the antidote to stagnation, a skill that allows us to continually learn, adapt, and better understand each other. Without it, we default to fixed positions, binary thinking, and conflict escalation.Curiosity means asking open-ended questions, exploring ideas we don’t initially agree with, and staying open to being surprised. For leaders, modeling curiosity invites that mindset across a team. It tells people their ideas matter—even if they’re different or incomplete.And while curiosity might sound like a soft skill, it has very real impacts on innovation, team cohesion, and ultimately, performance.Not subscribed? Let’s fix that, shall we? Subscribe for free to receive new posts by email. (No spam. I promise.)Time Pressure vs. Long-Term ThinkingWe also talked about time pressure. What happens when you're in conflict at work but feel like there's no time to sit down and work it out?Deb’s answer was clear: if you don’t make time for it now, you’ll pay for it later—probably with more time, stress, and friction. Trying to push through without dealing with the real issue often leads to bigger breakdowns down the line. On the flip side, making space for dialogue (even just a little) can result in more durable solutions.One of the ways to manage that time pressure, she said, is to get comfortable with not having immediate clarity. Sometimes the best thing a team can do is agree to keep talking, keep listening, and let the path forward emerge gradually.Culture, Communication, and Cross-Team CollaborationLater in the conversation, we got into cultural differences—across nationalities, disciplines, even departments. Deb’s background includes working with Israeli and Palestinian teens, and the lessons she learned there are surprisingly transferable to corporate teams.The core idea: everyone brings their own lens to every conversation. We all interpret language, data, and goals differently. That’s even true when we’re technically speaking the same language. (I learned this while teaching sailing to someone from the UK—turns out “quite good” doesn’t mean the same thing in both countries.)Within scientific companies, this plays out between technical teams and commercial teams, or between different functional areas. The solution? Again, it comes back to curiosity and creating space for people to explain their views before rushing to fix the “problem.”Deb made a powerful point: even when people don’t agree, they can still work together if they respect where the other is coming from. That opens up new ways forward.From Leads to Loyalty: Marketing with Relationship in MindFinally, I asked Deb to tie this all back to marketing. So many companies still operate with a “get me leads” mentality—but in reality, lasting impact comes from relationships, not transactions.She was clear: if you want lasting value, you need relational resilience. Short-term wins might feel good, but it’s long-term trust that gets you through hard times and keeps customers coming back. That mindset applies to internal culture, too. If you're only focused on extracting value from employees during their two-year tenure, you're missing the chance to build something better—something that retains talent and gets stronger over time.The Bottom LineThis conversation made me think more deeply about how we show up in teams—not just in crisis or disagreement, but every day. Deb’s framework of relational resilience gives us a better way to build cultures that support creativity, growth, and real collaboration.For marketers, for scientists, for managers, for anyone in business: this isn’t about being soft. It’s about being smart. It’s about recognizing that long-term thinking, curiosity, and vulnerability aren’t just nice-to-haves—they’re the foundation of meaningful progress.Your deepest insights are your best branding. I’d love to help you share them. Chat with me about custom content for your life science brand. Or visit my website. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit cclifescience.substack.com

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  32:27

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