AI Is Reshaping Drug Discovery and the FDA Is Onboard
SpaceDev has joined the AWS Partner Network (APN), Amazon Web Services’ global program for companies that build and deliver solutions on its platform.
It’s a step that formalizes what we’ve been doing for years: designing, building, and operating software systems that run on AWS infrastructure for companies in Latin America and abroad. It also introduces a clearer framework for how that work is validated, documented, and improved over time.
What the Partnership Represents
The AWS Partner Network is a structured system that requires partners to demonstrate technical capabilities, maintain trained and certified teams, and follow AWS architectural and security best practices.
Participation in the APN gives SpaceDev access to:
AWS training and certification programs for its engineering and architecture teams
Technical guidance aligned with AWS reference architectures
Validation paths that require documented experience, customer outcomes, and technical review
This matters for clients because it replaces informal claims of expertise with externally defined standards.
The Client Experience
Becoming an AWS Partner doesn’t change how SpaceDev approaches projects overnight. What it does change is the level of structure behind decisions that already influence cloud-based systems.
Projects built under the AWS Partner framework are expected to align with AWS principles around:
security and identity management
reliability and fault tolerance
scalability and performance under growth
cost control and operational visibility
These principles are embedded in AWS reviews, training materials, and partner validation programs, which require showing how systems are designed and operated in practice.
“AWS-Validated” Solutions
AWS doesn’t certify every individual application built by its partners, but it validates specific capabilities through programs such as service specializations and competencies.
When SpaceDev refers to AWS-validated work, it means:
systems designed according to AWS architectural best practices, and
delivery processes that are eligible for AWS validations, which require technical evidence and customer references.
The goal is consistency: fewer ad-hoc architectural choices and more repeatable, well-understood patterns.
The Bottom Line
As companies scale their digital operations, cloud infrastructure becomes harder to change and more expensive to get wrong. Architecture decisions made early tend to persist for years.
Joining the AWS Partner Network is part of SpaceDev’s effort to reduce that long-term risk for clients by aligning its cloud work with a widely adopted, externally governed framework rather than internal preferences alone.
A New Era in the Lab
Drug development has long relied on animal testing to evaluate a compound’s safety. But the process is slow, expensive, and often doesn’t translate well to human outcomes. Now, the FDA is pushing for a pivot. Within three to five years, animal studies could become the exception, not the rule.
The agency laid out its vision in an April roadmap: computational models, AI-based platforms, and human cell simulations could replace many animal tests—particularly for monoclonal antibody drugs. The potential payoff? Faster timelines, cheaper development, and eventually, more affordable drugs.
Who’s Leading the Charge?
Companies like Certara, Schrodinger, and Recursion Pharmaceuticals are already proving what’s possible.
Certara, which supports drugmakers working on infectious disease therapies, is using AI to simulate how drugs are absorbed, distributed, and whether they could cause toxic side effects. “We’re getting to the point where we don’t actually need to do [animal testing] anymore,” said Patrick Smith, president of drug development solutions at Certara.
Recursion accelerated a cancer drug candidate into clinical trials in just 18 months, less than half the industry’s 42-month average, using its AI-driven discovery platform.
Schrodinger, based in New York, merges AI with physics-based simulations to assess drug toxicology.
Analysts at TD Cowen and Jefferies predict these approaches could eventually cut both costs and development times by more than 50%. That’s a game-changer, considering it currently takes up to 15 years and $2 billion to bring a drug to market.
Old Giants, New Tricks
Legacy players aren’t sitting idle. Charles River Laboratories, one of the world’s largest research contractors, is investing heavily in “new approach methodologies” (NAMs). These include everything from AI modeling to human-based systems like organs-on-chips, tiny devices lined with living human cells that mimic organ function.
Charles River’s NAM portfolio is already pulling in around $200 million annually. Other innovators like InSphero are testing drug safety in 3D liver models made from lab-grown microtissues.
Will Animal Testing Disappear?
Not quite yet. While the FDA’s shift signals major change, experts agree that animal testing won’t vanish overnight. For now, a hybrid model is the most likely path forward: fewer animal studies, supplemented by advanced simulations and human-based models.
Under current FDA guidelines, monoclonal antibodies still require animal testing, typically involving 144 non-human primates per study, with each animal costing about $50,000. These studies can last up to six months, time and money the industry would love to save.
As Brendan Smith, biotech analyst at TD Cowen, puts it: “I don’t think we’ll get to a point immediately, in the near term, where all of a sudden, animal testing is gone entirely.”
The Bottom Line
AI isn’t just disrupting drug development, it’s redefining it. As computational tools become more powerful and regulatory agencies embrace innovation, drugmakers have a real shot at transforming how medicines are brought to market.
Faster. Cheaper. More humane.
That’s the future pharma is betting on.
