Raghu Peddapatla

Dr. Raghu Peddapatla

orcid

Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 December 2017 in Crystal Growth & Design
Verified
Journal Article
Open access
Vivek VermaVivek Verma
Vivek Verma
RPRaghu Peddapatla
Raghu Peddapatla
CCClare M. Crowley
Clare M. Crowley
ACAbina Crean
Abina Crean
PDPeter Davern
Peter Davern
BHB. Kieran Hodnett
B. Kieran Hodnett
This study is based on the heterogeneous nucleation of active pharmaceutical ingredients (APIs) in the presence of various excipients widely used in the pharmaceutical industry. Carbamazepine (CBMZ) was successfully crystallized in the presence of the following heterosurfaces: α/β-lactose, β-d-mannitol, microcrystalline cellulose, and carboxymethyl cellulose. The successful crystallization of CBMZ FIII in the presence of all the excipients was confirmed by powder X-ray diffraction and scanning electron microscopy, while CBMZ crystals’ apposition was confirmed using in situ scanning electronic microscopy-Raman. A pronounced improvement in the dissolution of CBMZ FIII was observed when crystallized in the presence of excipients when compared with CBMZ FIII recrystallized using the same conditions in the absence of the excipients. The isolated solids could be simply tabletted by direct compression upon mixing with the desired amount of disintegrant and lubricant. Hence employing this process could potentially streamline the downstream process in pharmaceutical industries and also increase the throughput with reduced cost.

7 July 2021 in Pharmaceutics
Verified
Journal Article
Open access
PDF file
RPRaghu Peddapatla
Raghu Peddapatla
GSGerard Sheridan
Gerard Sheridan
CSConor Slevin
Conor Slevin
SSShrikant Swaminathan
Shrikant Swaminathan
IBIvan Browning
Ivan Browning
ACAbina Crean
Abina Crean
Optimizing processing conditions to achieve a critical quality attribute (CQA) is an integral part of pharmaceutical quality by design (QbD). It identifies combinations of material and processing parameters ensuring that processing conditions achieve a targeted CQA. Optimum processing conditions are formulation and equipment-dependent. Therefore, it is challenging to translate a process design between formulations, pilot-scale and production-scale equipment. In this study, an empirical model was developed to determine optimum processing conditions for direct compression formulations with varying flow properties, across pilot- and production-scale tablet presses. The CQA of interest was tablet weight variability, expressed as percentage relative standard deviation. An experimental design was executed for three model placebo blends with varying flow properties. These blends were compacted on one pilot-scale and two production-scale presses. The process model developed enabled the optimization of processing parameters for each formulation, on each press, with respect to a target tablet weight variability of <1%RSD. The model developed was successfully validated using data for additional placebo and active formulations. Validation formulations were benchmarked to formulations used for model development, employing permeability index values to indicate blend flow.

29 November 2017 in Molecular Pharmaceutics
Verified
Journal Article
Closed access
RPRaghu Peddapatla
Raghu Peddapatla
MAM. Rizwan Ahmed
M. Rizwan Ahmed
CBCaroline A. Blackshields
Caroline A. Blackshields
MGMaria Jose Jose Sousa Gallagher
Maria Jose Jose Sousa Gallagher
SMSean McSweeney
Sean McSweeney
DFDara Fitzpatrick
Dara Fitzpatrick

23 March 2022 in Pharmaceutics
Verified
Journal Article
Open access
PDF file
RPRaghu Peddapatla
Raghu Peddapatla
CSConor Slevin
Conor Slevin
GSGerard Sheridan
Gerard Sheridan
CBCaoimhe Beirne
Caoimhe Beirne
SSShrikant Swaminathan
Shrikant Swaminathan
ACAbina Crean
Abina Crean
The ability to predict formulation behaviour at production scale during formulation design can reduce the time to market and decrease product development costs. However, it is challenging to extrapolate compaction settings for direct compression formulations between tablet press models during scale-up and transfer from R&D to commercial production. The aim of this study was to develop statistical process models to predict tablet tensile strength, porosity and disintegration time from compaction parameters (pre-compression and main compression force, and press speed), for three formulations, with differing deformation characteristics (plastic, brittle and elastic), on three tablet press models (one pilot-scale tablet press (KG RoTab) and two production-scale presses (Fette 1200i and GEA Modul P)). The deformation characteristics of yield pressure and elastic recovery were determined for the model placebo formulations investigated. To facilitate comparison of dwell time settings between tablet press models, the design of experiments (DoE) approach was 9 individual 16-run response surface DoEs (3 formulation × 3 press models), whose results were combined to create a polynomial regression model for each tablet property. These models predicted tablet tensile strength, porosity and disintegration time and enabled the construction of design spaces to produce tablets with specified target properties, for each formulation on each press. The models were successfully validated. This modelling approach provides an understanding of the compaction behaviour of formulations with varying deformation behaviour on development and commercial tablet press models. This understanding can be applied to inform achievable production rates at a commercial scale, during the formulation development.

20 November 2025 in Journal of Drug Delivery Science and Technology
Verified
Journal Article
Closed access
RKRohit Kumar
Rohit Kumar
MLMatthew K. Longtin
Matthew K. Longtin
JCJonathan V. Cummings
Jonathan V. Cummings
BPBhavin Parekh
Bhavin Parekh
MOMark A. Oliveira
Mark A. Oliveira
RCRenato Andrés Chiarella
Renato Andrés Chiarella

9 March 2026 in Molecular Pharmaceutics
Verified
Journal Article
Closed access
RPRaghu Peddapatla
Raghu Peddapatla
MAM. Rizwan Ahmed
M. Rizwan Ahmed
MSMaria J. Sousa-Gallagher
Maria J. Sousa-Gallagher
RKRohit Kumar
Rohit Kumar
SMSeán McSweeney
Seán McSweeney
ACAbina Crean
Abina Crean