Is SAS Only for Big Pharma?

In the past, it was common for small and mid-size life science companies to think of SAS as something only large pharmaceutical companies used. Many would plan to adopt SAS later, waiting until the organization was bigger, more mature, or had more resources.

But that mindset is shifting, more early-stage and growing biotech, medtech, and CRO organizations are starting to use SAS sooner, not because they want complicated systems, but because they need reliable, compliant, and scalable ways to work with data from the beginning.

Life science companies now face many of the same expectations as larger firms, even at an early stage; data needs to be accurate, traceable, and well-documented. As clinical, safety, and research data grows quickly and becomes hard to manage manually, regulators and partners expect consistent reporting. Any mistakes in data can lead to delays, rework, or compliance issues.

Spreadsheets and basic reporting tools can work for a while. But once data becomes regulated, shared across teams, or used for submissions, they can start to become risky.

What’s changed about SAS?

Fortunately, for small and midsize businesses, SAS has become much more accessible and affordable than it used to be. While SAS itself isn’t new, the way companies use and deploy it has changed significantly.

Smaller organizations no longer need to invest in large on-premise infrastructure. Today, SAS can run in cloud or hybrid environments and be implemented for just one or two specific use cases to start.

It’s also no longer necessary to build and maintain a full in-house team to support it. Many companies now work with partners, such as InfoPathways, to manage implementation, support, and future expansion, allowing their SAS environment to grow alongside the business without adding unnecessary complexity.

Why waiting can create problems

Many companies wait until data becomes overwhelming or until a regulatory deadline is approaching, and then try to implement SAS under pressure. That often leads to rushed implementations and messy migrations from older systems. Even post implementation, teams are bogged down by extra work to clean, document, and validate old data. This leads not just to higher stress for teams, but also higher risk for the business.

Starting earlier, even on a small scale, helps companies build better habits around data and avoid those painful transitions later.

Who should consider SAS now?

You don’t need to be a large organization, you should start thinking about SAS if you are:

• Running or planning clinical trials
• Preparing data for regulatory submissions
• Combining data from multiple systems or partners
• Spending a lot of time fixing or rechecking reports
• Worried about whether your data would hold up in an audit

If any of those sound familiar, it’s a good sign that your current tools may not be enough for what’s coming next. Let’s talk through your data challenges and determine whether SAS is the right fit for your organization.