Formulation and process · Process development
“Our crystallization yield is too low, and we don't know whether to cool or use an antisolvent.”
Crystallization process design: cooling or antisolvent
Whether a crystallization runs by cooling or with an antisolvent determines yield, solvent volume and effort during scale-up. CovaSyn computes solubility curves and mixtures up front, compares both routes and narrows down the solvents worth testing in the lab. You receive a traceable evaluation that your team reviews and decides on.
Starting point
When you need this
- Crystallization yield is too low because too much product stays in the mother liquor.
- For a new intermediate or API it is open whether to cool or precipitate with an antisolvent.
- A solvent has to be replaced, for ICH Q3C reasons or for sustainability, without losing yield.
- The product oils out when the antisolvent is added instead of crystallizing.
Result
What you get
Solubility curves
Solubility over temperature in the solvents considered, as the basis for the cooling route and the theoretical yield.
Cooling and antisolvent compared
Expected yield, saturation temperature, cooling rate and critical antisolvent fraction for both routes side by side, with miscibility of the pairs.
Narrowed-down solvents
A ranked list of suitable solvents and antisolvents with a note on the ICH Q3C class.
Report with the calculation path
Inputs, model and result are in the report, so your expert can trace and sign off every number.
Three ways
Yourself, together, or done for you
Run it yourself
Draw the molecule in the sketcher or use the tools through the CovaSyn MCP directly in Claude, ChatGPT or Cursor.
Go to MCPLearn it together
In a workshop your team learns how to answer questions like this with AI, cleanly and traceably.
See workshopsDone for you
We run the evaluation with our tools and deliver the finished report. Your expert reviews and signs off.
See Done-for-You
CovaSyn
The tools behind it
Deterministic calculations instead of guessed answers: the same tools we use for Done-for-You work are available to you directly.
Covasolve
Solubility prediction, solubility curves over temperature, solvent recommendation, mixtures, miscibility, and cooling and antisolvent crystallization.
Covachem
pKa values and a physicochemical profile, for example to check whether a pH shift or salt formation supports the crystallization.
Audience
Who it is for
For process development and CMC teams at CDMOs, generics manufacturers and specialty chemicals companies who design a new crystallization, improve its yield or replace a solvent.
What the computation does not replace
- Predictions do not replace measurement. They reduce the number of experiments; you confirm solubility and yield in the lab.
- Polymorphism, nucleation, the metastable zone and particle size are not captured by a calculation from structure; that needs experiments and data from your lab.
Insights
Read on
Cooling vs Antisolvent: Choosing the Isolation Route
Cooling vs antisolvent crystallization: how supersaturation is generated, when cooling simply cannot work, and a worked CovaSolv example: 0.0% vs 99.96%.
Read articleAntisolvent Crystallization Design: Pick the Route First
Antisolvent crystallization design in practice: how to choose antisolvent vs cooling, set the volume fraction, and predict yield before you touch.
Read articleSolvent Selection Under ICH Q3C: A Data Question
Solvent selection under ICH Q3C explained: what Class 1, 2 and 3 mean, the ppm limits, and how predicted solubility narrows the candidate list before lab.
Read articleGreen Solvent Substitution Without Losing Solubility
Green solvent replacement in pharma: rank ICH Q3C Class 3 alternatives to DCM and chloroform by predicted solubility before you book lab time.
Read articleSolubility Prediction Model Accuracy: How to Read It
Solubility prediction model accuracy explained: scaffold vs random splits, RMSE 0.689 on 4,193 held-out rows, and why apparent is not intrinsic solubility.
Read article
Questions
Common questions
Cooling or antisolvent crystallization: which fits better?
Cooling pays off when solubility rises steeply with temperature; then little remains in the mother liquor at the final temperature. If the solubility curve is flat, an antisolvent usually gives more yield but costs additional solvent. CovaSyn computes both routes for your molecule and shows which one promises the higher yield at acceptable solvent consumption.
How do I calculate crystallization yield?
Theoretical yield follows from the difference between the amount dissolved at the start and the solubility at the end, at final temperature or after antisolvent addition. Losses during washing and filtration come on top. CovaSyn calculates the theoretical yield from predicted solubilities as a starting point for your lab trials.
What to do when the product oils out with the antisolvent?
Oiling out often means supersaturation rises too quickly or the solvent pair is unfavourable. Slower addition, higher temperature, seeding or a different pair often help. CovaSyn compares alternative solvent pairs by solubility and miscibility; whether a pair actually crystallizes only the experiment shows.
Which solvent is suitable for crystallization?
A good solvent has high solubility at high temperature, low solubility at low temperature and a favourable ICH Q3C class. CovaSyn ranks solvents by these criteria and proposes suitable antisolvents with checked miscibility.
Who can design our crystallization for us?
CovaSyn does this as Done-for-You: you describe molecule and process in the intro call, we agree on data and scope, and you typically receive the report within 5 working days once we have your data. Handled confidentially from the start.
Can I run this myself?
Yes. In the sketcher you draw the molecule and see core data instantly; the solubility and crystallization tools are available through the CovaSyn MCP directly in your AI assistant.
Formulation and process
Related problems we solve
Solve a solubility problem before you run out of material
Our API won't dissolve properly, and we have been trying solvents for weeks.
See solutionDesign of experiments (DoE): from design to analysis
We have too many factors and too little material, and nobody on the team is sure which design fits.
See solutionProcess optimization and process capability (Cpk, Ppk)
Our Cpk is too tight, and we don't know which parameter drives the variation.
See solution
Next step
Tell us about your crystallization.
30 minutes on Microsoft Teams with the CovaSyn team. If it is not a fit, we will say so.