Expert Bioprocess Designer Suite

Describe it. Simulate it. Decide at the bench.

Seven bioprocess design apps, all powered by one chemistry engine — so you can try a hundred conditions before you commit material to eight. And when the pH lands somewhere you didn't expect, you see why, not just that it happened.

Join the beta Explore the apps

In beta now: Expert Buffer Designer, Expert Solution Operations Designer and Expert Bioreactor Designer.

pH against total volume for a 100 mL Protein A pool: 1 M acetic acid takes it from pH 4.2 down to 3.5 by about 116.5 mL, then Tris base at 1.5, 1 or 0.75 M brings it back to pH 7.8 at about 137, 147 and 157 mL. — A screenshot from Expert Solution Operations Designer. 100 mL of 20 g/L antibody in 50 mM acetate at pH 4.2, taken to pH 3.5 with 1 M acetic acid, then back to 7.8 with Tris base at 0.75, 1 or 1.5 M: one sweep, every point computed rather than interpolated. The weaker the base, the more volume it takes to get there: 41, 31 and 21 mL of 0.75, 1 and 1.5 M Tris per 100 mL of pool.

What changes when you can simulate it

Understand, experiment, scale

01 · Understand

Better understanding.

Watch the Donnan effect pull your retentate pH off target, or ionic strength shift a pKa. The mechanism is visible, so a surprise becomes something you can reason about — and explain to someone else.

02 · Experiment

Better experiments.

Ask the questions you'd never spend material on. Forty conditions sweep in about three seconds, so “what if we ran it colder” costs nothing but curiosity — and your DOE arrives with a reason behind every point.

03 · Scale

Better processes.

What you learn at 10 mL carries forward: the same solutions and the same chemistry, into skid design, buffer supply and the campaign schedule.

The assistant

Describe it in words. The numbers still come from the model.

Describe the process the way you'd describe it to a colleague, and the assistant builds the design, runs it through the simulation, and reads the result back in a sentence. The chart and the table are right there beside it, so you are never taking its word for anything.

The assistant drives the model; it doesn't do the arithmetic. Every number on screen comes from the same first-principles engine you would have driven by hand — and if you change an input, the results are flagged stale rather than left to be misread.

What you type

“50 mM phosphate with 150 mM sodium chloride at pH 7.2, made up at 4 °C”

What it sets up · Expert Buffer Designer

Buffer system: Phosphate
Buffer concentration: 50 mM
Target pH: 7.20
Salt: Sodium chloride, 150 mM
Temperature: 4 °C

One chemistry engine · seven apps

Ask, explore, characterize

Seven different tools, not seven views of one — sharing the chemistry that has to agree between them. Each answers a question you actually have. Find the one that sounds like your week.

App	Who it's for	The question it answers	Status
Expert Buffer Designer	PD · Formulation	What will this buffer's pH actually be at 4 °C instead of 25 °C — and how much has it moved?	In beta
Expert Solution Operations Designer	PD · MSAT	After I titrate, dilute and condition a pool — what is actually in the tank now?	In beta
Expert Bioreactor Designer	USP · Cell culture	How will pH control behave once the cells start making acid — and will my base addition keep up?	In beta
Expert Buffer Stock Blending Designer	MSAT · Facility	Can my skid actually make this buffer from the stocks I hold — and is blending it cheaper than preparing it?	Coming soon
Expert UF/DF Designer	Formulation · DSP	Why did my retentate pH drift away from the diafiltration buffer — and what buffer should I have used instead?	Coming soon
Expert Chromatography Designer	DSP · Purification	For a protein with this pI, where should I start the gradient — and should this be CEX or AEX?	Coming soon
Expert Process Designer	MSAT · Manufacturing	Across a twelve-batch campaign, do I run out of buffer or tank space — and on which day?	Coming soon

Why you can trust the answer

Computed, not fitted

Every number comes from a charge-balance solve on the full ionic speciation — not a fixed pKa. Because it is computed rather than fitted, a molecule nobody has characterized yet is modeled as well as a familiar one, which is precisely when you have the least data and the most experiments to plan.

We check the engine against published measurements, and we say where it stops being reliable. See the science →

Design sweep

2.9 s

for 40 conditions, on an ordinary server — down from 20.6 s before parallelization. Fast enough that exploring costs you nothing.

Bring your process. Leave with a characterized one.

The beta runs in the browser, with each person's work in its own private workspace. It's free during the beta.

Join the beta How the models work