By Andrew Donald, Director of Engineering, Optima Partners
Life sciences has never relied on data more than it does today. Whether it’s sequencing genomes or training AI models for drug discovery, much of that progress now runs on the cloud. It gives researchers the scale, flexibility, speed and global reach that on-premise systems can’t deliver.
Inefficiencies in how those resources are used can quietly slow science down, with key analysis take longer than they should, model trainings that burn cycles without convergence, or scattered trial datasets stored all adding up to wasted time that scientists could be spending on discovery.
That cost is significant, with Flexera’s 2025 State of the Cloud Report showing enterprises waste an average of 27–32% of their spend. In life sciences, where R&D budgets already stretch across years of trials and regulatory hurdles, that level of waste risks holding back the very science patients depend on.
Why It Happens
The problem rarely comes from one obvious fault. It’s usually dozens of small decisions that seem reasonable at the time:
- Running queries written for another engine that act as anti-patterns in BigQuery, technically valid, but hugely inefficient.
- Writing a pipeline that scans an entire dataset when only a subset is needed.
- Leaving a compute cluster running after an analysis finishes.
Individually, these choices look harmless, however, multiplied across labs, trials, and functions, they add up quickly.
At Optima, we have seen the same patterns first-hand across different industries. In one review, a single query was running as a full data refresh every day. It looked routine, yet it was costing nearly $18,000 per month. With a small rewrite, it delivered the same results for less than $400. Through bioXcelerate AI, our dedicated life sciences division, we are applying the same proven strategies to help partners uncover hidden costs, streamline operations, and accelerate research impact.
The real challenge is visibility. Cloud providers will tell you what you have spent, but rarely why; Without that insight, teams end up firefighting, cutting costs in one quarter, only to see them creep back the next.
The Limits of Quick Fixes
Many organisations try to fix the issue with tactical clean-ups: shutting down old environments, tweaking infrastructure, or running one-off optimisation scripts. That buys time, but it doesn’t change the habits and processes that caused the waste in the first place. Inefficiencies reappear, often in the most business-critical areas like research pipelines or AI model training.
In life sciences, this is more than a budget problem. Every dollar wasted on unnecessary compute is a dollar not spent on accelerating a trial, scaling an AI model, or investing in new therapies. Those investments ultimately mean faster access to life-changing treatments for patients. Efficiency becomes a driver of innovation, not just an exercise in cost control.
Cloud CEO: A Systematic Approach
Cloud Cost Efficiency Optimisation (Cloud CEO) brings technical rigour together with practical changes in how teams work, so efficiency becomes part of everyday delivery rather than a one-off exercise.
- Detect: We uncover inefficiencies at their source, not just on the bill. That means identifying the pipelines, queries, and workflows that quietly drive-up costs.
- Optimise: Our engineers work alongside delivery teams to re-write, resize, and redesign, fixing issues where they happen.
- Embed: We close knowledge gaps, strengthen governance, and adapt operating models so the same problems do not return.
Cloud CEO isn’t a clean-up project; it’s a discipline that helps organisations innovate at pace while keeping costs under control.
Proven Impact of Cloud CEO
The impact of tackling cloud inefficiency shows up quickly. In one engagement, our review of a client’s cloud estate revealed around 30% code inefficiency, including a single query costing more than $17K per month. By addressing these patterns, we helped the organisation reduce its annual cloud spend by around 8%. In another case, analysing just a hundred of the worst performing queries in a large international business identified up to $15 million of annual waste. Practical fixes to reduce this wastage can often be implemented in a matter of weeks.
These numbers only tell part of the story, when inefficiencies are removed, data scientists can spend less time firefighting and more time focusing on research. Leaders gain confidence that budgets are being used where they matter most, allowing organisations to free up resources to invest in discovery, AI, and next-generation manufacturing.
When cloud spend is predictable and efficient, the science moves faster, and that’s what really matters.
Building the Foundations for the Future
At Optima & bioXcelerate, our mission is to help life sciences organisations power growth through sustainable data design and AI-led innovation. Cloud CEO is one way we do that.
For this industry, efficiency isn’t about penny-pinching. It’s about building the foundations needed to run larger datasets, train more ambitious models, and move promising therapies from bench to bedside more quickly.
Cloud efficiency isn’t only a technical challenge; it’s a business priority. Done well, it delivers more than savings, it creates space for innovation, gives leaders confidence, and helps organisations take on the next wave of scientific discovery.
Contact Optima Partners today to learn more.
