6 min read

Not your average data room

Data rooms are central in biotech: not only do they underpin key events like fundraising, asset licensing, and M&A, but they also have the power to actively inform R&D roadmap decisions, if used correctly. In this Kaleidoscope post, we dive into what makes data rooms special in the industry. If anything here resonates, please reach out!


  • Data rooms are a valuable company resource. They serve as strategic tools to communicate important information about a company's IP, assets, and plans, to various stakeholders. A well-structured data room can catalyze progress through critical inflection points like fundraising or partnership.
  • Biotech data rooms are unique. The information they contain - things like key experimental results or project timelines - need to be referenced with regularity. Internally, for driving R&D projects forward, and externally, for communicating progress and aligning stakeholders.
  • Unique requirements necessitate new ways of working. A biotech data room is a dynamic place – a living, breathing, collaborative IP repository. Traditional tools and approaches for managing this (Powerpoints, spreadsheets, Dropbox, etc.) are poor fit-for-purpose and likely costing your team.

Earlier this year, a16z wrote a great piece on virtual data rooms being the “unsung heroes of biotech”. In that piece, they gave a shout out to Bessemer’s Morgan Cheatham, who wrote a similar Substack post on the anatomy of a good data room, including what information biotech and life science companies should include when fundraising and how that information should be structured. Both articles are great primers on how, if used correctly, data rooms can be leveraged by founders as strategic assets to control the company’s narrative and de-risk the company for external partners – namely investors. 

Lactiga is one example in the life science space, of how a well-organized, creative data room gave investors confidence in their traction without any ‘traditional’ traction proof points. And while this, along with the above two pieces, are good examples of how to craft a good data room, they beg the question: what’s special about a biotech data room?  

Biotech is a uniquely complex space that requires vertically-aware software tools. These specialized demands and ways of operating extend to data rooms, too. In this industry, data rooms look very different and serve different critical purposes that go well beyond fundraising. This has important implications on what it means to build a data room in biotech, what a powerful data room looks like, and what it should enable you to do. 

When it comes to traditional software, data rooms are something you typically build when you’re raising money. Investors and lawyers will go through your customer contracts and financials during their diligence process and will then come to a decision on whether they want to invest. Once your fundraising round closes, your data room moves out of the spotlight. It’s a relatively static place that acts as a periodic snapshot into your company’s health – and this snapshot doesn’t have to be meaningfully reconstructed until the next time you raise money. 

The same isn’t true in biotech – companies in this space often reference critical data on a weekly basis. BD partnerships, pharma collaborations, asset sales, clinical prep, board updates, financing events –  all of these depend on stakeholders having a reliable window into your data, with access to the latest information on your assets. They need to be able to see where you’re at with critical milestones; and since biotech is such a data-heavy team sport, this will constantly change with the amount of data you’re generating and the insights different teams are extracting from that data. Moreover, different stakeholders will need to see different data to different levels of granularity, depending on whether they’re external or internal, or what experiments are most relevant to them.

This is a completely different use case for data rooms compared to fundraising diligence assistance. 

And yet, biotechs are trying to use the same general purpose, static tools to build data rooms that underpin a very different, dynamically evolving, continuous process. We speak with companies on a weekly basis that, by their own admission, don’t have an effective way of collecting and organizing key information because their processes and systems are all over the place. They’re often spending 10+ hours a week filtering through and patching together different parts of Google Docs, spreadsheets, powerpoints, and ELNs, in an attempt to centralize the critical information they need in order to keep important internal and external stakeholders aligned. On top of disparate systems that lack integration and centralization, information is siloed within different teams, meaning another chunk of time goes towards emailing people to ask for updates. 

The general workaround we hear from companies is that they’ll end up creating a massive, unruly Powerpoint, Sharepoint, or Dropbox file and will regularly ask team members to drop files or screenshots into it. These files are not searchable, are not indexed, and are not labeled. And beyond being extremely inefficient, this method is a lot more prone to risks of phantom results appearing, that can severely compromise an organization’s data integrity. 

So when we talk about what a truly powerful data room looks like, the industry status quo simply doesn’t cut it. Biotech data rooms shouldn’t be a place where you dump files and forget about them after, when that information is what you’re regularly using to inform critical business and R&D decisions. Like the a16z piece said, data rooms have the potential to be extremely strategic assets and you want them to guide your opinions and roadmap as a company. To treat them as an afterthought where you occasionally drop and forget about files, or to rely on jerry-rigged, Frankenstein solutions consisting of hundreds of outdated Powerpoint decks and spreadsheets, is a mistake. It leaves a lot of significant value on the table. 

Instead, data rooms should be living, breathing, searchable and referenceable repositories of what IP you’re generating, why it matters, and who needs to know. They should be a powerful way to tap into your data and answer questions like what’s the latest information we have on this compound? or which asset looks most promising? and share that information with the right stakeholders at the right time. This visibility and availability is what’s missing in data rooms today, and it means whenever a company is at a critical juncture, they have to painfully find the relevant information from scratch every time. The frequency, nature, and gravity of these use-cases - weekly and monthly leadership, board, or partnership meetings - creates certain expectations and demands that cannot effectively be fulfilled by tools made for very different circumstances. 

What’s also often overlooked is that the more visibility you’re able to provide as a company, the stronger your relationships are. By keeping your partners, board, and investors up to date and aligned on the progress you’re making, you’re keeping them engaged and excited by that progress, which creates an inherently positive flywheel where they feel more involved and more inclined to help. Similarly, when you centralize data in one place, you keep your internal team focused and aligned on the bigger mission. Naturally, you’ll want to maintain granular control over what stakeholder sees what type of data, which is why you’ll want to make sure you have the right permissions management in place.

These results are only possible if we stop trying to make static, traditional, fundraising-centric data rooms work in situations they’re not well-suited for, and instead move towards adopting a more nuanced definition of data rooms in biotech: as dynamic assets that should always be up-to-date and that can easily be referenced and leveraged to help inform critical decision-making. And much like how it’s now the norm for accounting software to plug into your Quickbooks, Stripe, and other accounts to pull live financial data, we’re taking the same approach for biotech at Kaleidoscope. 

With Kaleidoscope, teams get a centralized hub that is R&D-aware: a platform that is plugged into the various other tools and data sources you may have, that stays automatically updated with the new information you’re generating, and that makes it easy to find your most important data and keep your most important stakeholders in the loop. Moreover, Kaleidoscope gives you the ability to create different functional views to communicate about your data, depending on the purpose at hand – from high-level decision dashboards or project status trackers, to more granular asset comparison views or parameter-based filters/sets. Not your average data room. 

If you want to chat more about anything we wrote, or you’re interested in finding a way to work together, let us know!