Case Study 1 – Increase understanding of API crystallisation and improve consistency of PSD for a commercial product
Project Objective Increase understanding of API crystallisation and improve consistency of PSD for a commercial product: Approach
- Identified success criteria for ideal API characteristics: D90 range, modality, crystal habit, filtration behaviour.
- Assessment of process using JMP software determined complex crystallisation with multiple factors interacting with each other.
- Fractional factorial design to generate parameter conditions for 9 experiments using JMP.
- Key findings used to implement recommendations for manufacturing on scale.
- Output measured using laser light scattering (Malvern), scanning electron microscopy, Morphologi G3 image analysis, leaf filtration.
Output Provide recommendations for on scale manufacturing
Case Study 2 – Determine proven acceptable range (PAR) for micronisation of a product to meet customer requirements
Project Objective Determine proven acceptable range (PAR) for micronisation of a product to meet customer requirements Approach
- Central composite experimental design investigating mill pressure and product feed rate
- Influence of input material assessed by performing confirmatory runs using different inputs at coarse and fine ends of PAR
Output
- Established PAR and operating parameter set points
- Determined input PSD has no impact on output
Case Study 3 – Crystallisation Optimisation for Improved Deliquoring Rates in a Filter Dryer
Problem Statement Variable bottleneck cycle times (97-161 hr, target is 91 hr) due to deliquoring rates during isolation of a commercial intermediate on a filter dryer. The process team requested that the crystallisation be investigated to determine if material with more suitable powder properties could be generated.
- Fine hair-like needles observed post nucleation
- Material blinding filter cloth → very long deliquoring times.
- Limited development space for a filed commercial product.
- Proposed the introduction of temperature cycles to the cooling step (Ostwald Ripening) to promote growth of material.
- Proof of concept experiment completed to demonstrate benefits.
- Consultation with process team and engineer followed by repeat experiment optimised for plant conditions.
Outcome
- Filtration rates monitored in the lab using a pressurised leaf filter and analysed using SEM and light microscopy.
- Slurries were filtered at 1 bar gauge pressure with 10 mm filter cloth.
- Filtration reduced from > 40 seconds to 2-5 seconds via introduction of temperature cycles.
- Comparable material quality and losses to the mother liquor
Case Study 4 – Improved Consistency of Unmilled API PSD
Problem Statement
- Variable PSD observed for unmilled API due to inconsistent nucleation and growth.
- Potential for dendritic growth resulted in dryer attrition and bimodal PSD.
- Modality and PSD observed using Morphologi-G3 and Malvern.
Attrition during extended crystallisation hold and agitated drying
Dendritic-columnar crystals
Presence of fines
- An increase in variability had been observed over time, therefore a project was initiated to understand cause of variability and improve consistency.
- A number of experiments performed using Radley’s AutoMATE reactor/RX10 with FBRM probe.
Factor investigated in the laboratory included:
- Powder properties of seed
- Temperature of solution on receipt to crystalliser
- Seeding temperature
- Anti-solvent addition time
- Cooling profile/time
Crystallisation solution was determined to be highly supersaturated leading to variability in desupersaturation. Allowing more time for material to desupersaturate resulted in less dendritic growth. Recommendations included:
- Target temperature to be maintained during transfer of batch to the crystalliser.
- Adjustment of solvent matrix in seed slurry
- Recommended RPM for agitation in the crystalliser (based on CFD study)
Batch Temperature before and after transfer to crystalliser
Case Study 5 – X-Ray Powder Diffraction (XRPD) Analysis
XRD is a powerful, non-destructive and rapid technique for analyzing a wide range of materials (1 µm to 100 mm), including metals, polymers, catalysts, plastics, pharmaceuticals etc.
Key Features
- Vital method for investigation and characterization of crystalline materials in the QC and R&D Laboratories.
- Best qualitative method for identification of a phase purity of unknown bulk composition.
- Minimal sample preparation required.
- The data interpretation is straightforward.
Instrument Details
- X-ray Tube: the main source of X Rays.
- Incident-Beam Optics: condition the X-ray beam before it hits the sample.
- Goniometer: a platform that holds and moves the sample, optics, and detector.
- Sample Holder: Holds the sample in place and rotates it if required.
- Air Scatter: controls the size of the viewed diffracting sample surface, so as to improve diffraction resolution and minimize cross-contamination.
- Receiving-side Optics: condition the X-ray beam after it has encountered the sample.
- Detector: count the number of X Rays scattered by the sample.
Operation of XRD
- X-rays are generated in a cathode ray tube by heating a filament to produce electrons, accelerating the electrons toward a target by applying a voltage, and bombarding the target material (Cu, λ = 1.54 wavelength) with electrons.
- The generated X-rays are directed towards the sample, and the diffracted rays are collected by the detector (See Figures 2 & 3).
- A key component of all diffraction is the angle between the incident and diffracted rays (2θ). A typical powder patterns data is collected at 2θ from ~5° to 70°, angles that are present in the X-ray scan.
- A detector records and processes this X-ray signal and converts the signal to a count rate which is then output to a device such as a printer or computer monitor.
Figure 2: A schematic illustration of operations of XRD main components.
Figure 3: A schematic diagram for coherent diffraction, satisfying Bragg’s Law.
Interpretation
- The peak intensities in the diffractogram are determined by the distribution of atoms within the lattice. As a result, the X-ray diffraction pattern is the fingerprint of periodic atomic arrangements in a given sample.
- Phases with the same chemical composition can have drastically different diffraction patterns.
- The position and relative intensity of a series of peaks can be used to match experimental data to reference data in a database.
References
- USP <941> : X-ray diffraction USP monograph, Current Edition
A – Identification of polymorphic forms
Problem statement:
- After work up from the reaction mixture, it is possible to get different polymorphic forms of a material.
Impact:
- Different polymorphs can effect the solubility, dissolution rate, bioavailability, and physical stability of the drug substance.
Identification Technique:
- PXRD is the best technique to identify different polymorphic forms in the reaction mixture [USP <941>].
Results:
- Comparison of sample diffractogram with the Ref Std diffractograms confirmed that the sample is present in Form D (For more details, see Figure 4).
- The agreement in the 2θ-diffraction angles between the sample and the Ref Std is within 0.2°.
- Peak relative intensities between sample and Ref Std may vary considerably due to preferred orientation effects.
Figure 4: Ref Std Form D (red line); Ref Std Form B (blue line): Sample (black line)
B – In-Process Production Support
XRD analysis can be used for production support to confirm the correct Form is being produced Conversion from Form 2 to preferred Form 1 occurs during drying; XRD testing was performed as an “In-Process” test to confirm complete conversion to Form 1 Red arrow point out to undesired Form 2; present in the First Drying Sample and not present in Final Drying Sample
