scholarly journals Flux-Based Formulation Development—A Proof of Concept Study

2022 ◽  
Vol 24 (1) ◽  
Author(s):  
Szabina Kádár ◽  
Petra Tőzsér ◽  
Brigitta Nagy ◽  
Attila Farkas ◽  
Zsombor K. Nagy ◽  
...  
Keyword(s):  
Large Scale ◽  
Small Volume ◽  
Drug Product ◽  
Dosage Forms ◽  
Drug Formulation ◽  
Screening Methods ◽  
Formulation Development ◽  
First Case

AbstractThe work aimed to develop the Absorption Driven Drug Formulation (ADDF) concept, which is a new approach in formulation development to ensure that the drug product meets the expected absorption rate. The concept is built on the solubility-permeability interplay and the rate of supersaturation as the driving force of absorption. This paper presents the first case study using the ADDF concept where not only dissolution and solubility but also permeation of the drug is considered in every step of the formulation development. For that reason, parallel artificial membrane permeability assay (PAMPA) was used for excipient selection, small volume dissolution-permeation apparatus was used for testing amorphous solid dispersions (ASDs), and large volume dissolution-permeation tests were carried out to characterize the final dosage forms. The API-excipient interaction studies on PAMPA indicated differences when different fillers or surfactants were studied. These differences were then confirmed with small volume dissolution-permeation assays where the addition of Tween 80 to the ASDs decreased the flux dramatically. Also, the early indication of sorbitol’s advantage over mannitol by PAMPA has been confirmed in the investigation of the final dosage forms by large-scale dissolution-permeation tests. This difference between the fillers was observed in vivo as well. The presented case study demonstrated that the ADDF concept opens a new perspective in generic formulation development using fast and cost-effective flux-based screening methods in order to meet the bioequivalence criteria.

How “The Three Rules” guide strategy and investment decisions at Deloitte Consulting LLP

2015 ◽  
Vol 43 (3) ◽  
pp. 7-14 ◽  
Author(s):  
Jim Moffatt
Keyword(s):  
Design Methodology ◽  
Large Scale ◽  
Investment Decisions ◽  
Decision Makers ◽  
Research Project ◽  
Content Type ◽  
First Case ◽  
Practical Implications ◽  
Thought Leadership

Purpose – This case example looks at how Deloitte Consulting applies the Three Rules synthesized by Michael Raynor and Mumtaz Ahmed based on their large-scale research project that identified patterns in the way exceptional companies think. Design/methodology/approach – The Three Rules concept is a key piece of Deloitte Consulting’s thought leadership program. So how are the three rules helping the organization perform? Now that research has shown how exceptional companies think, CEO Jim Moffatt could address the question, “Does Deloitte think like an exceptional company?” Findings – Deloitte has had success with an approach that promotes a bias towards non-price value over price and revenue over costs. Practical implications – It’s critical that all decision makers in an organization understand how decisions that are consistent with the three rules have contributed to past success as well as how they can apply the rules to difficult challenges they face today. Originality/value – This is the first case study written from a CEO’s perspective that looks at how the Three Rules approach of Michael Raynor and Mumtaz Ahmed can foster a firm’s growth and exceptional performance.

X-ray Powder Diffraction Spectroscopy as a Robust Tool in Early Predicting Bioavailability of Pharmaceutical Formulation Containing Polymorphic Drug Substance

2020 ◽  
Vol 10 (3) ◽  
pp. 250-254
Author(s):  
Abhishesh K. Mehata ◽  
Deepa Dehari ◽  
Senthil R. Ayyannan ◽  
Madaswamy S. Muthu
Keyword(s):  
Powder Diffraction ◽  
Drug Product ◽  
3D Structure ◽  
X Ray Diffraction ◽  
Formulation Development ◽  
Lower Phase ◽  
X Ray ◽  
Drug Products ◽  
Physical Form

: X-ray powder diffraction (XRPD) is a unique, solid-state analytical tool used to study the 3D structure of small or macromolecules by their x-ray diffraction or scattering patterns. X-ray diffraction by a crystal reflects the periodicity of crystal architecture; any imperfections within the crystal architecture can be easily identified by its poor diffraction pattern. Recently, an open crystallography database reported that more than 85 % of drug compounds are crystalline and exist in different polymorphic states. Physicochemical properties of pharmaceutical drug products composed of active pharmaceutical ingredients (APIs) and excipients are interdependent on the physical state and forms in which APIs are distributed in excipients that determine the in-vivo and ex-vivo performance of the product. Amorphous APIs have relatively higher dissolution and bioavailability than crystalline form but with lower phase stability. During the formulation development and storage phase, the conversion is higher that largely impacts the bioavailability of the drug product. In this manuscript, we have presented the case study of itraconazole and apigenin; both are crystalline APIs, that, with the help of solid dispersion technology, are converted into amorphous drug products with enhanced oral bioavailability. The realtime monitoring of the physical form of API in the formulation was possible with the help of XRPD and other supporting data obtained from differential scanning calorimeter (DSC), which can be correlated with the dissolution and in-vivo performance of the formulation.

Enabling Multi-Robot Cooperative Additive Manufacturing: Centralized vs. Decentralized Approaches

2021 ◽  
Author(s):  
Saivipulteja Elagandula ◽  
Laxmi Poudel ◽  
Wenchao Zhou ◽  
Zhenghui Sha
Keyword(s):  
3D Printing ◽  
Large Scale ◽  
Small Scale ◽  
Scale Problem ◽  
Problem Case ◽  
Large Scale Problem ◽  
First Case ◽  
Novel Approach ◽  
Multi Robot

Abstract This paper presents a decentralized approach based on a simple set of rules to carry out multi-robot cooperative 3D printing. Cooperative 3D printing is a novel approach to 3D printing that uses multiple mobile 3D printing robots to print a large part by dividing and assigning the part to multiple robots in parallel using the concept of chunk-based printing. The results obtained using the decentralized approach are then compared with those obtained from the centralized approach. Two case studies were performed to evaluate the performance of both approaches using makespan as the evaluation criterion. The first case is a small-scale problem with four printing robots and 20 chunks, whereas the second case study is a large-scale problem with ten printing robots and 200 chunks. The result shows that the centralized approach provides a better solution compared to the decentralized approach in both cases in terms of makespan. However, the gap between the solutions seems to shrink with the scale of the problem. While further study is required to verify this conclusion, the decrease in this gap indicates that the decentralized approach might compare favorably over the centralized approach for a large-scale problem in manufacturing using multiple mobile 3D printing robots. Additionally, the runtime for the large-scale problem (Case II) increases by 27-fold compared to the small-scale problem (Case I) for the centralized approach, whereas it only increased by less than 2-fold for the decentralized approach.

scholarly journals Into the thirteenth Month: A Case Study on the Outbreak Analytics and Modeling the spread of SARS-CoV-2 Infection in Pune City, India

2021 ◽  
Author(s):  
Joy Monteiro ◽  
Bhalchandra Pujari ◽  
Sarika Maitra Bhattacharrya ◽  
Anu Raghunathan ◽  
Ashwini Keskar ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Information Dissemination ◽  
Public Access ◽  
Accurate Information ◽  
Time Data ◽  
Outbreak Response ◽  
First Case ◽  
And Control

With more than 140 million people infected globally and 3 million deaths, the COVID 19 pandemic has left a lasting impact. A modern response to a pandemic of such proportions needs to focus on exploiting all available data to inform the response in real-time and allow evidence-based decision-making. The intermittent lockdowns in the last 13 months have created economic adversity to prevent anticipated large-scale mortality and relax the lockdowns have been an attempt at recovering and balancing economic needs and public health realities. This article is a comprehensive case study of the outbreak in the city limits of Pune, Maharashtra, India, to understand the evolution of the disease and transmission dynamics starting from the first case on March 9, 2020. A unique collaborative effort between the Pune Municipal Corporation (PMC), a government entity, and the Pune knowledge Cluster (PKC) allowed us to layout a context for outbreak response and intervention. We report here how access to granular data for a metropolitan city with pockets of very high-density populations will help analyze, in real-time, the dynamics of the pandemic and forecasts for better management and control of SARS-CoV-2. Outbreak data analytics resulted in a real-time data visualization dashboard for accurate information dissemination for public access on the epidemic's progress. As government agencies craft testing and vaccination policies and implement intervention strategies to mitigate a second wave, our case study underscores the criticality of data quality and analytics to decode community transmission of COVID-19.

scholarly journals Integrating XMALab and DeepLabCut for high-throughput XROMM

2020 ◽  
Author(s):  
JD Laurence-Chasen ◽  
AR Manafzadeh ◽  
NG Hatsopoulos ◽  
CF Ross ◽  
FI Arce-McShane
Keyword(s):  
Large Scale ◽  
Fold Increase ◽  
X Ray ◽  
Marker Tracking ◽  
Markerless Tracking ◽  
Automatic Batch ◽  
Major Bottleneck ◽  
Proper Context

ABSTRACTMarker tracking is a major bottleneck in studies involving X-ray Reconstruction of Moving Morphology (XROMM). Here, we tested whether DeepLabCut, a new deep learning package built for markerless tracking, could be applied to videoradiographic data to improve data processing throughput. Our novel workflow integrates XMALab, the existing XROMM marker tracking software, and DeepLabCut while retaining each program’s utility. XMALab is used for generating training datasets, error correction, and 3D reconstruction, whereas the majority of marker tracking is transferred to DeepLabCut for automatic batch processing. In the two case studies that involved an in vivo behavior, our workflow achieved a 6 to 13-fold increase in data throughput. In the third case study, which involved an acyclic, post mortem manipulation, DeepLabCut struggled to generalize to the range of novel poses and did not surpass the throughput of XMALab alone. Deployed in the proper context, this new workflow facilitates large scale XROMM studies that were previously precluded by software constraints.

scholarly journals Evaluation of Excipient Risk in BCS Class I and III Biowaivers

2022 ◽  
Vol 24 (1) ◽  
Author(s):  
Melissa Metry ◽  
James E. Polli
Keyword(s):  
Drug Product ◽  
Scale Up ◽  
Drug Formulation ◽  
Product Regulatory ◽  
Drug Bioavailability ◽  
Drug Products ◽  
Fda Guidance ◽  
Regulatory Guidance

AbstractThe objective of this review article is to summarize literature data pertinent to potential excipient effects on intestinal drug permeability and transit. Despite the use of excipients in drug products for decades, considerable research efforts have been directed towards evaluating their potential effects on drug bioavailability. Potential excipient concerns stem from drug formulation changes (e.g., scale-up and post-approval changes, development of a new generic product). Regulatory agencies have established in vivo bioequivalence standards and, as a result, may waive the in vivo requirement, known as a biowaiver, for some oral products. Biowaiver acceptance criteria are based on the in vitro characterization of the drug substance and drug product using the Biopharmaceutics Classification System (BCS). Various regulatory guidance documents have been issued regarding BCS-based biowaivers, such that the current FDA guidance is more restrictive than prior guidance, specifically about excipient risk. In particular, sugar alcohols have been identified as potential absorption-modifying excipients. These biowaivers and excipient risks are discussed here.

scholarly journals Optimal sizing of a distributed energy system with thermal load electrification

2020 ◽  
Vol 197 ◽  
pp. 01006
Author(s):  
Pietro Lubello ◽  
Guglielmo Vaccaro ◽  
Carlo Carcasci
Keyword(s):  
Thermal Load ◽  
Large Scale ◽  
Energy Systems ◽  
Power Production ◽  
Electricity Production ◽  
Distributed Energy ◽  
Optimal Sizing ◽  
First Case ◽  
The Impact

Renewable energy systems (RES) are currently being deployed on a large scale to meet the ambitious sustainable development goals for the next decades. A higher penetration of sustainable means of power production passes through the diffusion of RES-based distributed energy systems. The hybridization of such systems and their integration with Energy Storage Systems (ESS) can help improve reliability and level the mismatch between power production and consumption. In this paper, a novel modular tool for the simulation of distributed energy systems is presented by means of its application to a case study. The considered system is composed by PV modules, ESS and heat pumps. The optimal sizing of the components for self-consumption has been obtained through an electricity production cost minimization. A comparison between two different configurations has been conducted: in the first case, the thermal load is completely satisfied by a natural gas-fired boiler, while in the latter case, part of the thermal load is satisfied by a heat pump. The results have highlighted the impact of ESS on the economics of distributed energy systems and how the investment in such systems, in conditions similar to the case study, can be more easily sustained if a share of the total energy consumption of the unit is shifted from the thermal to the electrical part.

Anti-tuberculosis drug combination for controlled oral delivery using 3D printed compartmental dosage forms: From drug product design to in vivo testing

2017 ◽  
Vol 268 ◽  
pp. 40-48 ◽  
Author(s):  
Natalja Genina ◽  
Johan Peter Boetker ◽  
Stefano Colombo ◽  
Necati Harmankaya ◽  
Jukka Rantanen ◽  
...  
Keyword(s):  
Product Design ◽  
Drug Combination ◽  
Oral Delivery ◽  
Drug Product ◽  
Dosage Forms ◽  
In Vivo Testing ◽  
3D Printed ◽  
Drug Product Design

scholarly journals Segmental-Dependent Solubility and Permeability as Key Factors Guiding Controlled Release Drug Product Development

Pharmaceutics ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 295 ◽  
Author(s):  
Milica Markovic ◽  
Moran Zur ◽  
Noa Fine-Shamir ◽  
Ester Haimov ◽  
Isabel González-Álvarez ◽  
...  
Keyword(s):  
Controlled Release ◽  
Product Development ◽  
Drug Product ◽  
Immediate Release ◽  
Class Ii ◽  
Distribution Coefficients ◽  
Analysis Model ◽  
Formulation Development

The main factors influencing the absorption of orally administered drugs are solubility and permeability, which are location-dependent and may vary along the gastrointestinal tract (GIT). The purpose of this work was to investigate segmental-dependent intestinal absorption and its role in controlled-release (CR) drug product development. The solubility/dissolution and permeability of carvedilol (vs. metoprolol) were thoroughly studied, in vitro/in vivo (Octanol-buffer distribution coefficients (Log D), parallel artificial membrane permeability assay (PAMPA), rat intestinal perfusion), focusing on location-dependent effects. Carvedilol exhibits changing solubility in different conditions throughout the GIT, attributable to its zwitterionic nature. A biorelevant pH-dilution dissolution study for carvedilol immediate release (IR) vs. CR scenario elucidates that while the IR dose (25 mg) may dissolve in the GIT luminal conditions, higher doses used in CR products would precipitate if administered at once, highlighting the advantage of CR from the solubility/dissolution point of view. Likewise, segmental-dependent permeability was evident, with higher permeability of carvedilol vs. the low/high Peff marker metoprolol throughout the GIT, confirming it as a biopharmaceutical classification system (BCS) class II drug. Theoretical analysis of relevant physicochemical properties confirmed these results as well. A CR product may shift the carvedilol’s solubility behavior from class II to I since only a small dose portion needs to be solubilized at a given time point. The permeability of carvedilol surpasses the threshold of metoprolol jejunal permeability throughout the entire GIT, including the colon, establishing it as a suitable candidate for CR product development. Altogether, this work may serve as an analysis model in the decision process of CR formulation development and may increase our biopharmaceutical understanding of a successful CR drug product.

scholarly journals Exploratory Assessment of the Limiting Extended Kalman Filter Properties

2013 ◽  
Vol 14 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Constantinos Antoniou ◽  
Alexandra Kondyli ◽  
Georgia-Maria Lykogianni ◽  
Elias Gyftodimos
Keyword(s):  
Kalman Filter ◽  
State Space ◽  
Extended Kalman Filter ◽  
Large Scale ◽  
State Space Models ◽  
Dynamic State ◽  
Gain Matrix ◽  
First Case ◽  
Kalman Gain

Abstract Most of the methodologies for the solution of state-space models are based on the Kalman Filter algorithm (Kalman, 1960), developed for the solution of linear, dynamic state-space models. The most straightforward extension to nonlinear systems is the Extended Kalman Filter (EKF). The Limiting EKF (LimEKF) is a new algorithm that obviates the need to compute the Kalman gain matrix on-line, as it can be calculated off-line from pre-computed gain matrices. In this research, several different strategies for the construction of the gain matrices are presented: e.g. average of previously computed matrices per interval per demand level and average of previously computed matrices per interval independent of demand level. Two case studies are presented to investigate the performance of the LimEKF under the different assumptions. In the first case study, a detailed experimental design was developed and a large number of simulation runs was performed in a synthetic network. The results suggest that indeed the LimEKF algorithm is robust and - while not requiring the explicit computation of the Kalman gain matrix, and thus having vastly superior computational properties - its accuracy is close to that of the “exact” EKF. In the second case study, a smaller number of scenarios is evaluated using a real-world, large-scale network in Stockholm, Sweden, with similarly encouraging results. Taking the average of various pre-computed Kalman Gain matrices possibly reduces the noise that creeps into the computation of the individual Kalman gain matrices, and this may be one of the key reasons for the good performance of the LimEKF (i.e. increased robustness).

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