Optimizing your biomanufacturing isn’t always straightforward.
We can help.
If you could hear what your cell culture was saying to you, would you listen?
We’ve been there. Another cell culture flask that didn’t produce the exact bioactive compounds in the right fashion. Or the pH changed a bit too much overnight and killed all the cells.
Creating the right conditions for growing cells isn’t easy. Your unsupplemented RPMI media isn’t going to always be the best growing condition for your genetically modified CHO cell line. What if you knew what your cells needed for optimal growth?
Traditional media optimization is a long, painstaking process to find the best media composition for your cells. Now, there’s something better than that.
“Culture media should boost yield — not waste your time.”
Culture Media Simulator
Adjust concentrations to find the metabolic "Sweet Spot".
Do you know what's in your media?
Historically, media contained undefined components such as serum. These components don't have defined compositions, and introduce variability to your process. Modern optimization focuses on Chemically Defined (CD) media, where every molecule is known.
Energy Sources
Glucose and Glutamine are the primary fuels, but excess leads to toxic Lactate and Ammonia.
Amino Acids
The building blocks of protein. Depletion of a single essential amino acid halts production.
Trace Elements
Vitamins, minerals (Zn, Se, Cu), and growth factors act as critical co-factors for enzymes.
Why should I optimize my media?
> 20%
Higher Yield
Increases cell yield substantially, pushing production efficiency.
80%
Lower Costs
Significantly lowers development costs by streamlining material usage.
66%
Faster Speed
Reduces development time dramatically, accelerating time to market.
Quality by Design
Gain deep biological insights that strictly conform to the QbD principle for regulatory success.
Bonus Professional Consultation
Get direct access to expert guidance to tailor the optimization process to your specific cell line needs.
Evolution of Methodology
Choose a strategy to see how optimization approaches have changed.
One Factor At a Time (OFAT)
The scientist changes the concentration of one component while keeping all others constant. Once the "best" level is found, they move to the next.
Drawbacks
- Misses component interactions
- Labor intensive & slow
- Often finds a "local optimum" not global
Design of Experiments (DoE)
Statistical software creates a matrix of experiments where multiple factors are varied simultaneously. This reveals how components interact.
Advantages
- Uncovers complex interactions
- Data-efficient (fewer runs)
- Finds the true Global Optimum
Computational Modeling
Computational model maps out cell metabolism to identify metabolic bottlenecks, unlocking culture media performance with key benefits
Advantages
- Faster development time
- Lowers development costs
- Provides biological insights compliant with Quality by Design(QbD)
The Optimization Roadmap
Identify Bottlenecks
Analyze spent media to identify metabolites limiting growth.
Predictive ML modeling
Accelerate development with computational metabolic analysis.
Recommend Components
Identify key metabolites and provide high-performing formulations.
Scale-Up
Validate process in large bioreactors to ensure scalability.