From The Trenches

By Abbas Kazimi, CEO of Nimbus Therapeutics, as part of the From The Trenches feature of LifeSciVC

The Japanese Zen term shoshin means “beginner’s mind”. It’s the discipline of approaching familiar territory with fresh eyes and openness to see what may have changed. For an expert, this is not easy, because expertise tempts you to apply tried and true assumptions to new ideas.

Drug discovery may need a little more shoshin right now.

The pace of progress at the intersection of AI and medicine has been remarkable. New scientific workbenches, evolving protein-design systems, broad generative chemistry platforms, and increasingly capable coding agents have fueled large financing rounds, high-profile appointments, and a steady news cycle of ambitious predictions.

Yet for those of us who have spent our careers discovering and developing medicines, the honest reaction is complicated. There is excitement and curiosity, but also a quieter set of questions:

How much of this is hype? How is this all getting financed? Is AI truly new, or a more compelling description of computational approaches we have used for years? Do we understand why drug candidates fail well enough to know where AI can help? And, where are the medicines?

From my perspective as a drug hunter, the question is no longer whether AI can augment drug discovery. The question is what prevents us from effectively accessing these tools, learning to use them well, and applying them to scientific questions that matter.

A More Grounded AI Moment

Anthropic’s recent launch of Claude Science is an important signal of where the field is heading. The ambition is no longer AI as a chatbot that summarizes literature, but AI as an active participant in scientific work that could change how researchers search, analyze, code, model, and collaborate.

Across the industry, leading pharmaceutical companies are making significant investments to embed AI into the fabric of drug discovery. Bristol Myers Squibb recently announced plans to build what it describes as the most powerful AI factory in life sciences with NVIDIA, following Eli Lilly’s own investment in dedicated AI infrastructure and deployment. These investments are not just larger computing clusters. They reflect a recognition that AI infrastructure, secure access to proprietary scientific data, and the ability to deploy advanced models at enterprise scale are becoming strategic capabilities for modern pharmaceutical R&D.

But the path from better models to better medicines is not automatic. Derek Lowe, the medicinal chemist behind the long-running In the Pipeline blog, put it most memorably. Responding to Intel’s Andy Grove, who argued that drug discovery should take a page from the rapid acceleration of the semiconductor field, Lowe retorted that biology is not a system we have built from the ground up with fully understood governing rules. It is the product of billions of years of evolution. Better computation can help us navigate that complexity, but it does not make the complexity disappear.

That same tension appears in recent comments from Anthropic CEO Dario Amodei and Nobel laureate Jennifer Doudna, co-discoverer of CRISPR-Cas9. Amodei has been explicit that the impact of AI will depend on researchers learning to use it and organizations changing how they work. Doudna has cautioned against assuming that AI will replace the human ingenuity behind transformative discovery. Both perspectives lead to the same conclusion: more capable AI will not make biology any less difficult. It may accelerate discovery, but it will not remove the need for experimentation or judgment.

Holding those two ideas together, with confidence in AI’s potential and humility about what biology has yet to yield, may be one of the most important leadership challenges of this moment.

Different Roles in the AI-Enabled Drug Ecosystem

As powerful AI models become broadly available, what will differentiate one drug discovery organization from another?

The current conversation often groups very different organizations under the broad label of “AI drug discovery.” The boundaries are not perfectly clean, and some companies span more than one role, but I find it useful to distinguish among three parts of the ecosystem:

Tool builders create the models, software, predictive systems, and computational platforms that hopefully expand what drug discovery teams can do. Companies such as Isomorphic Labs and Chai Discovery are aiming to create tangible value by advancing the foundational models and platforms that enable AI-driven drug discovery.

Drug discovery companies, Nimbus included, integrate biology, chemistry, computation, experimentation, translational science, and portfolio judgment to create differentiated molecules and advance them into early clinical development.

Development and commercialization companies translate promising molecules into medicines through late-stage trials, regulatory approval, manufacturing, and patient access. This is where large pharmaceutical companies have historically excelled.

Nimbus is fundamentally a drug discovery company.

Throughout Nimbus’s history, our strategy has never been to build novel technologies ourselves. It has been to identify the technologies that create the most scientific leverage, integrate them fully into our discovery engine, and build proprietary capabilities only where they create lasting advantage.

We have applied that philosophy for years from computational chemistry and physics-based molecular design to machine learning, coding agents, scientific assistants, and connected workflows. Our partnership with AWS follows the same principle: rather than building foundational AI infrastructure of our own, the collaboration gives our scientists a secure, scalable environment to develop and deploy AI capabilities across active discovery programs.

The Advantage Is Learning Speed

Infrastructure enables discovery. It does not, by itself, differentiate discovery. When tools become broadly available, the advantage will shift from the tools themselves to how quickly an organization turns those tools into validated learning and better scientific decisions.

The speed that matters is the learning cycle:

AI can compress that cycle by moving teams more quickly from question to evidence to decision. However, the advantage isn’t simply speed. It’s the speed of validated learning and every output still has to survive contact with the bench and the clinic. Without judgment, speed can simply generate more noise. Used with discipline, AI can help teams learn earlier, stop sooner, and advance better molecules.

Speed is also relative. Drug discovery typically represents only the first four years of a decade or more of R&D, while late-stage clinical development accounts for most of the overall timeline and cost.

Accelerating early discovery is valuable, but improving the quality of decisions and advancing better molecules into development may have an even greater impact by reducing the risks that dominate the later stages of R&D.

What It Looks Like in Practice

In an earlier LifeSciVC post, I wrote that owning the learning loop matters more than owning the lab. AI makes that argument even more relevant.

At Nimbus, these tools are extending what great scientists can accomplish by shortening the distance between a scientific question and validated learning. This is not aspiration; it’s happening across our programs now.  AI is embedded across the learning loop, from ideation and design through prediction, experimentation, and decision-making.

In one active program, our team built and deployed a custom pKa model in nine days to resolve a hERG-related design liability. In another, coding agents helped rewrite and extend a large pharmacophore and molecular shape-matching codebase in about a week, compressing work that might previously have taken months.

Across the portfolio, predictive ADME and property models increasingly guide which compounds we synthesize. Physics-based methods and machine learning are being combined to explore differentiated chemical space. We are also integrating agentic interfaces directly into our discovery workflows, enabling scientists to bring together literature, experimental data, calculations, specialized software, proprietary models, and internal decision frameworks through a common interface. These computational chemistry agents do more than make individual tools easier to use but rather help orchestrate the full workflow between a scientific question, a calculation, an experiment, and the next decision.

Our path has been evolutionary rather than a single leap. We began by giving teams broad access to tools such as Claude and Perplexity and then expanded into literature, patents, competitive intelligence, coding, and scientific synthesis. We are now developing reusable, domain-specific agents for target assessment, computational chemistry, medicinal chemistry, and other high-value workflows.

This is the advantage of embedding AI into a drug discovery company. The technology is tested continuously against active programs where the tools and programs improve each other through experimental feedback and validation.

What Actually Matters

The industry will continue to debate what should be called AI-designed, AI-enabled, AI-native, computational, generative, or agentic. Some distinctions are useful, but none is the final measure. What matters is whether these tools help us ask sharper questions, expose failure earlier, and move the right molecules forward.

At Nimbus, we believe they can, and the tools we have already deployed are making an impact. Rather than forcing AI into the center of an existing workflow to validate its use, we are extending what great drug hunters do and strengthening the learning loop around them.

As AI capabilities become widely available, the winners will not be the organizations that generate the most output. They will be the ones that approach new technologies with shoshin to learn faster, and turn what they learn into medicines that matter for patients.

Many thanks for the contributions and editorial advice from Daniel Price (Vice President, Computational Chemistry & Structural Biology, Nimbus) Cindy Fung (Vice President, Corporate Affairs & Communications, Nimbus), Peter Tummino (President, Research & Development, Nimbus), and Bruce Booth, (Partner, Atlas Venture).

Comment

By Julia Pian, Senior Associate at Atlas Venture, as part of the From The Trenches feature of LifeSciVC

Before attending my first board meeting, I fondly remember imagining a board as the “Room Where It Happens,” yearningly described by Aaron Burr in the musical Hamilton. Over the last few years, after serving as an observer on 10 boards across the Atlas portfolio, and almost 50 board meetings later, my view of the board room has gained significant nuance, but there are still some aspects of being in a board room that could use demystifying.

The LifeSciVC canon on boards is rich. Bruce has compiled an encyclopedia of advice for startup boards; Samantha Truex has written thoughtfully on how to build a board and how to decide whether to join one; Ivana Magovcevic-Liebisch has reflected on the independent director’s role; and Rene Russo has covered how to make board meetings a strategy sync rather than a time sink. But comparatively little has been shared about the topic of being a board observer, despite their widespread presence in board rooms across our industry. A 2024 NVCA survey found that 82% of venture capitalists now utilize board observer seats in one way or another.

To get the mechanics out of the way, board observers do not have the typical voting rights or fiduciary duty of a board director but do have the right to attend board meetings and receive associated highly confidential materials. There are different types of observers, including strategic investors (where corporate policy may limit the ability to hold a director seat), minority shareholders, or, what we’ll focus on today, venture capital “plus-1s”. Mark Suster of Upfront Ventures lays out the nuances of these different observer phenotypes in his memorably titled blog “Why You Should Avoid Adding ‘Board Observers’ to Your Startup’s Board”.

Frankly, board observership sometimes gets a bad reputation, as an additional body in what can be a crowded board room for a CEO or board chair to manage. Each board is a unique animal, and I certainly won’t claim that observers are uniformly net positive to boards, but as Mark Suster acknowledges, venture capital is an apprenticeship business. I would advocate that board observer roles should be seen, at least in part, as investments in developing an experienced next generation of venture capitalists, board directors, management teams, and generally leaders of our industry. My goal with this post is to share my reflections on what observers, directors, and management teams can do to turn observers in your boardroom from a bug (or “fly on the wall”) into a feature. How can a board observer support the board of directors and management team as well as grow their own skillset? These reflections are distilled from my experiences as an observer at companies that cover the spectrum of private biotech (discovery to clinical stage, seed to crossover funded) and conversations with board directors and CEOs who have generously shared their experiences working with board observers over the years. I am deeply grateful to the Atlas team and portfolio management teams for the opportunity to learn from and contribute to an incredible group of companies.

Onboarding: don’t be a stranger

There is an oft-quoted adage that “there should never be surprises in a board meeting”, and that wholeheartedly applies to your presence and identity as a board observer. I’ve twice been in board meetings where a board member has asked if the meeting has been compromised because there is someone they don’t recognize on the Zoom, only for that person to actually be a new “plus-1” board observer who was added last-minute.

Avoid this scenario at all costs by starting your role as a board observer well before your first meeting. If you haven’t already connected with the CEO, reach out and introduce yourself over email and request a quick 15–30-minute chat before the first board meeting for brief introductions. You can also use that time to ask a few questions to set yourself up for success:

• What are your expectations for a board observer before, during, and after board meetings?
• Is there a cadence of communication between meetings with the board directors (+/- observers) that you typically follow?
• Who else on the team would you recommend that I connect with?
• Anything I should know about how you run your board meetings (and board dinners)?
• And finally, what can I do in my role to best support the company?
  • Are there perspectives on investor sentiment or the emerging competitive landscape that I can proactively share?
  • Are there fund-level resources or networks that I can help the company tap?
  • Are there talent needs that I can help fill through my network (perhaps deeper into the bench than the typical C-suite referrals you might get from a board director)?

This early rapport not only helps avoid an awkward first meeting but can also be incredibly important when difficult conversations arise in the board room. For example, it can be even tougher for a CEO to discuss a sensitive pending leadership team change or talk through year-end comp in exec session when there is someone they have never met before silently listening in. A half-hour coffee chat can go a long way in building trust and respect.

Consider opportunities to meet one-on-one with other members of the management team beyond the CEO. Whether it’s other members of the leadership team or perhaps the CEO’s right-hand person in corporate development/strategy, connecting with the broader team can strengthen the partnership and collaboration that you can have with the company over time. However, before broadly sending calendar invites to the whole team, be mindful of the CEO’s preferred communication style with the board and the demand on the team’s time while they are actually operating the company!

Finally, have an onboarding meeting with the partner/board director you are working with. You can use the same questions above to help set up a positive working partnership on the company. At the same time, you can catch up on the key points of discussion from the last one or two board meetings and get a sense of what aspects of the company the board director is most excited about or views as the most risky.

Before the meeting: dive into the details

Good observership has many shared principles with good directorship, and the best example of that is the importance of being prepared for board meetings. One of the universal asks I’ve heard when discussing observership with both CEOs and board directors is that they want observers to dive deep into the details: fully digest the board materials, bring up relevant external data or comparables and, occasionally, source external expert or KOL opinions to help shape key strategic decisions. Yes, that means looking into the details of the tox package, knowing the latest on CMC progress, and pressure testing those projected clinical trial enrollment curves. Generate key questions or points in advance to discuss with your director so that these thoughts can be previewed with the CEO in the pre-board call and can then sharpen the discussion during the board meeting.

Where being an observer can differ from the director role is in serving as a lower-stakes sounding board for the management team/CEO. Ideas that aren’t ready for the full board, such as a new indication to add to a platform pipeline or an early partnering concept, can be previewed and pressure-tested with an observer first. Not only can the observer bring their own experience and expertise to evaluating some of these early ideas, but you can also share institutional knowledge that can help shape how the CEO might ultimately present the idea to the board. For example, has a given indication been on the fund’s 2026 bingo card and is therefore likely to be received positively or is there scar tissue around that indication due to previous tough development experiences (rational or otherwise!)?

At the meeting: quality over quantity

I’ll start this section by caveating that the dynamics of each board room are different, and expectations may differ on how observers should best contribute their thoughts and ideas. However, a guiding principle to follow when adding your voice to the board room is quality over quantity. Thoughtful contributions or questions that add a new perspective or new data point and enhance strategic conversations are often genuinely welcome.

Do consider piping up with clarifying questions on data and company plans or adding context that your experience or training gives you unique insight into, particularly if it relates back to the broader questions being debated during the meeting. On the other hand, absolutely don’t lead the board down a rabbit hole that isn’t strategically relevant at the time, ask gotcha questions that are adversarial to the management team, or unveil a controversial strategic recommendation that catches the team and board alike by surprise. Using your words wisely (and sometimes sparingly) goes a long way in building up your credibility as a contributing member of the board.

For questions or smaller points that don’t make the cut to be aired during the main meeting, consider other more casual opportunities to discuss these items with the team and other board members. For example, a lull in conversation at a board dinner or coffee break can be a great time to ask that detailed question about the secondary endpoint measurement mechanics, ancillary screening assay, or fourth program that is good to know, but not immediately strategically relevant.

After the meeting: keep the momentum going

Board meetings often generate action items, from additional analysis to offered connections and introductions. Where possible and appropriate, keep the momentum going, and offer to send that email introduction to another portfolio company facing a similar issue, or share data points or resources with the team that might help with the strategic analysis. Just as with board directors, much of an observer’s value accrues between meetings.

Both internally to the venture fund and externally, an observer is also an ambassador for the company, just as a board director is. Be thoughtful in how you represent the company’s progress and promise, as well as ongoing risks, and ensure that your elevator pitch about the company is tight and aligns with what management and board members are communicating.

The long game: observe and learn!

While the rest of this post has been focused on ways that a board observer can try to add value to the company, I’d like to close by highlighting the opportunity that being an observer can present for introspection and growth. Board observership is truly an unparalleled experience not to be squandered.

First, as the title of the role suggests, observe! As Bruce and Mark Suster have previously highlighted, there are different Board Director phenotypes that often emerge. Which phenotype do you find yourself most falling into and how can you proactively improve your thought processes and communication style? What style of comments do you find particularly convincing and hope to emulate? My own quick reflections:

• I’ve found the most impactful questions from great directors are those that pull the discussion back into the higher-level “so what?” For example, we’re all scientists at heart and want to generate more data, but the best questions drill down into what the value of the data will be internally for decision making and externally for creating strategic optionality.
• Often in a lull during the CEO-only session, a director pipes in with “How is the team doing? How are they working together?” This boilerplate question is more important than it seems, and almost always yields important discussions that either confirm a healthy organization executing at its best or allow the board to proactively address personnel issues before they’ve reached a boiling point.
• The most convincing comments succinctly lay out the assumptions required to come to that decision point. In other words, what set of conditions needs to be true for us to look back and think that this was the right decision? Not only is this framing persuasive, it also highlights the key variables at play and enables more grounded discussion where all parties are on the same page in terms of the facts and premise being interrogated.

Finally, use this opportunity to practice putting a stake in the ground on tough strategic decisions. If a question is being discussed at the board level, that means it is not straightforward and there is no correct answer. Getting in the reps on gaining conviction in a path forward is important in developing strategic leadership muscles. Then, put yourself in the shoes of various members of the board and think through how their incentives, experience, and information they bring to this decision may differ.

Done well, the observer role is mutually beneficial to the board, company, and observers themselves. The learning and contributions of a board observer reinforce each other: the more useful you make yourself, the more access and context you earn, and the sharper your judgment becomes. These experiences will shape you regardless of which seat in the boardroom you occupy next.

Acknowledgements: Many thanks to the Atlas partners, investment team, and portfolio company management teams who have generously offered advice and support for me as a board observer over the years. Special gratitude to Emily Conley, Niranjan Kameswaran, Cyrus Moyazeni, and Arthur Tzianabos.

Comment