Rayca Science Formulation and delivery
Excipients, polymers and lipids are molecules too. Rayca models them with the same physics and learning it applies to the active ingredient, connects them to your formulation history, and lets what the medicine must become shape the molecule while its chemistry can still change.
The problem
Formulation knowledge is among the least digitised in R&D. And it arrives after the molecule is fixed.
Where research and development loses time and evidence today, read against how Rayca changes each point.
Knowledge outside the record
Compositions, process parameters and stability outcomes sit in batch records, notebooks, study reports and the experience of a few individuals. Little of it is connected to the molecule it describes.
Formulation as part of the record
Compositions, processes and outcomes are linked to the molecule and its solid form, so they can be searched, compared and learned from.
Development by iteration
Excipient screens, prototype batches and stability studies are explored largely empirically, and each round takes weeks or months to read out.
Informative studies first
Compatibility, stability and performance are modelled before the bench, so the studies your team runs are the ones most likely to change a decision.
Discovery and development disconnected
Candidates are often nominated with little regard for route, dose and dosage form. Formulation then inherits properties that discovery could have changed.
The product profile upstream
Route, dose and intended form become design constraints during lead optimisation, while the chemistry is still flexible.
Delivery systems treated as recipes
Lipid and polymer compositions are frequently optimised by screening, with assembly, release and intracellular behaviour poorly resolved at the molecular level.
Delivery systems as molecular systems
Lipids, polymers and excipients are molecules. Rayca models their assembly and behaviour with the same physics and learning it applies to the active ingredient.
Designed back from the patient 01
Formulation inherits a molecule that was designed for it.
The medicine, in cross-section
From the molecule outProduct profile
- Route
- Dose
- Frequency
- Dosage form
Set during lead optimisation
01Molecule
02Solid form
03Formulation
04Delivery
05Patient
The active ingredient, designed against its target.
Formulation as data 02
Formulation experience compounds across programs.
Formulation record
Batches, compositions and outcomes01Gather the batches
02Resolve compositions
03Link the outcomes
Records, notebooks and study reports, read where they live.
Compatibility and stability 03
Stability studies spend their time confirming good choices.
Excipients and stress
Compatibility, then degradation01Model interactions
02Map degradation
03Calibrate
04Choose prototypes
The active ingredient against candidate excipients.
Enabling formulations 04
Enabling approaches are chosen on mechanism, not habit.
Spring and parachute
Supersaturation from an amorphous dispersion01Mix drug and carrier
02Hold the dispersion
03Spring and parachute
Miscibility of drug and polymer, simulated.
Delivery systems as molecules 05
Carrier design moves from screening recipes to understanding them.
A lipid nanoparticle, modelled
Assembly, response and releaseComposition
- Ionisable lipid
- Sterol
- Helper lipid
- Stealth lipid
Next to examine
Filled: tested. Blue: proposed next.
01Compose
02Assemble
03Respond
04Learn
Ionisable, helper, structural and stealth lipids with the payload.
From release to exposure 06
Formulation decisions are read in terms of exposure.
Formulation to exposure
Release, absorption, exposure01Release
02Absorption
03Exposure
04Return
Predicted dissolution of the formulation.