PHARMACEUTICALS
up effects and the effects of process or tooling variations .
These simulations also enable the scientific fingerprinting of actives , excipients and formulations . The objective of compaction simulation is to predict the equipment parameters needed to obtain robust tablets with the desired properties , without wasting expensive API or conducting large-scale trials .
Along with compaction behaviour , powder flow properties affecting powder processability are critical . Powder characterisation for processrelated investigations can be achieved using a powder rheometer , which quantifies a powder ’ s shear properties and behaviours as transitions from no-flow to flow . The data can also be used to assess the sensitivity of formulations to press speed and can guide formulation changes based on material characteristics .
DEM is another powerful tool for understanding the behavior of powder during processing and for designing scale-up strategies . By providing a mechanistic understanding of particle dynamics in powder systems , DEM , coupled with CFD , offers critical insight for such pharmaceutical unit operations as pan coating , spray drying , fluid bed processing and continuous manufacturing .
Common applications in pharma include blending , tablet breakage , die filling , milling , granulation tablet compaction , powder fluidisation and coating . With respect to blending , for example , DEM can inform optimal loading operations or fill volume to improve mixing performance during scale-up and overall process efficiency .
Predicting API properties & PK
Oral drug absorption is a complex process influenced by many factors , including the physico-chemical properties of the drug , formulation characteristics , and interplay of gastrointestinal physiology and biology . The use of in silico models to investigate ADME-PK properties of NCEs has become increasingly common in early discovery and preclinical development , where it is used to inform candidate selection , ADME characterisation and translation of exposure and effect .
In recent years , the value of these modelling tools has extended beyond early development . Population PK and pharmacodynamic modelling is becoming a clinical development differentiator by facilitating first-inhuman dose selection and providing mechanistic evaluations of ADME data . These models can also aid in predicting bioequivalence , as well as PK in special populations , such as paediatrics .
For each phase of development , ADME-PK modelling leverages existing data to build increasingly robust models ( Table 1 ). Some of the key applications include :
• Dose bioavailability
• Sensitivity analysis
• Guidance on formulation design
• Mechanistic in vitro / in vivo correlations
• Understanding food effects
• Physiologically based PK modelling of preclinical & clinical data
• Predicting animal & first-in-human doses
• Assessment of drug – drug interactions
Conclusion
Thanks to the availability of highquality datasets and advanced analytical capabilities , these and other predictive modelling tools and capabilities are helping to accelerate progress in drug development and clinical research and reduce some of the inherent scientific , economic and delivery risks .
Realising the full potential of the technology requires more than access to the tools . It also demands careful selection of in silico strategies and a deep understanding of how to interpret and derive the most valuable insights from the data . ●
Sanjay Konagurthu
SENIOR DIRECTOR , SCIENCE & INNOVATION , PHARMA SERVICES
THERMO FISHER SCIENTIFIC k + 1 541 639 7210 J sanjay . konagurthu @ thermofisher . com j www . patheon . com
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