Arun Giridhar

Dropwise additive manufacturing of pharmaceutical products for solvent-based dosage forms.

In recent years, the US Food and Drug Administration has encouraged pharmaceutical companies to develop more innovative and efficient manufacturing methods with improved online monitoring and control. Mini-manufacturing of medicine is one such method enabling the creation of individualized product forms for each patient. This work presents dropwise additive manufacturing of pharmaceutical products (DAMPP), an automated, controlled mini-manufacturing method that deposits active pharmaceutical ingredients (APIs) directly onto edible substrates using drop-on-demand (DoD) inkjet printing technology. The use of DoD technology allows for precise control over the material properties, drug solid state form, drop size, and drop dynamics and can be beneficial in the creation of high-potency drug forms, combination drugs with multiple APIs or individualized medicine products tailored to a specific patient. In this work, DAMPP was used to create dosage forms from solvent-based formulations consisting of API, polymer, and solvent carrier. The forms were then analyzed to determine the reproducibility of creating an on-target dosage form, the morphology of the API of the final form and the dissolution behavior of the drug over time. DAMPP is found to be a viable alternative to traditional mass-manufacturing methods for solvent-based oral dosage forms.

A workflow modeling system for capturing data provenance

Abstract A workflow is an abstraction of the steps associated with the underlying work process and is typically modeled as a directed graph. The workflow concept under its various manifestations has been used to model applications in diverse areas, including project planning, manufacturing, scientific experiments, execution of computer software, and publishing. While the Open Provenance Model Core Specification had laid the foundation for defining the key concepts in a workflow, a simplified high level graphical representation of a workflow that is widely applicable is not available. In this paper we describe a novel general framework for building workflows and implementing the associated actions, which will facilitate understanding of work processes across multiple disciplines. As such, most work processes are organized hierarchically with well defined control and management responsibilities. This framework will facilitate integration and coordination of activities across associated domains. Additionally, it will act as a template to refer to the associated metadata as well as reference to access the instance data from archives of completed workflow cases. When a specific case is in progress, a finite state machine will guide the user through the steps and provide up to date information about the current state. We describe the main building blocks in the framework, their functionalities and illustrate the integration of workflows between an experimental and a scientific process.

Intelligent Process Management for Continuous Operations in Pharmaceutical Manufacturing

Abstract Over the last fifteen years, pharmaceutical manufacturing has moved cautiously from an exclusively batch-oriented system towards continuous production. Sensing and instrumentation for continuous production have improved much in that time, but the development and adoption of new process management technologies have lagged compared to instrumentation due to various barriers. In this work, we describe those barriers and present solutions in achieving continuous closed-loop operations in pharmaceutical manufacturing.

Real-Time Process Management Strategy for Dropwise Additive Manufacturing of Pharmaceutical Products

PurposeThis paper presents a real-time process management (RTPM) strategy for Dropwise Additive Manufacturing of Pharmaceutical Products (DAMPP), a mini-manufacturing method for pharmaceutical dosage forms. The semicontinuous, small-scale nature of DAMPP allows for more automation and control than traditional large-scale batch pharmaceutical manufacturing processes and can be used to manufacturing drug products with precise amounts of active pharmaceutical ingredients (API), suitable for production of high-potency drug products or individualized medicine.MethodsThe RTPM strategy for DAMPP consists of advanced process control to ensure that every dosage unit meets quality specifications. We use temperature control systems and an imaging system linked to a LabVIEW automation program.ResultsThe system is successful in controlling deposition of both solvent-based and melt-based dosage forms. It controls process and product temperature and monitors each drop visually. It records data pertinent to each deposited drop, determines the drop volume and thus API amount deposited, and automatically detects and diagnoses process faults.ConclusionsWith a proper automation, control, and monitoring strategy, DAMPP is a viable manufacturing method for pharmaceutical dosage forms.

Drop-on-Demand System for Manufacturing of Melt-based Solid Oral Dosage: Effect of Critical Process Parameters on Product Quality

ABSTRACTThe features of a drop-on-demand-based system developed for the manufacture of melt-based pharmaceuticals have been previously reported. In this paper, a supervisory control system, which is designed to ensure reproducible production of high quality of melt-based solid oral dosages, is presented. This control system enables the production of individual dosage forms with the desired critical quality attributes: amount of active ingredient and drug morphology by monitoring and controlling critical process parameters, such as drop size and product and process temperatures. The effects of these process parameters on the final product quality are investigated, and the properties of the produced dosage forms characterized using various techniques, such as Raman spectroscopy, optical microscopy, and dissolution testing. A crystallization temperature control strategy, including controlled temperature cycles, is presented to tailor the crystallization behavior of drug deposits and to achieve consistent drug morphology. This control strategy can be used to achieve the desired bioavailability of the drug by mitigating variations in the dissolution profiles. The supervisor control strategy enables the application of the drop-on-demand system to the production of individualized dosage required for personalized drug regimens.

Real-time Process Management in Particulate and Pharmaceutical Systems

Abstract A real-time process management (RTPM) system is equivalent to an automatic control system for running a production plant continuously while maintaining product quality. In pharmacautical manufacturing, such a system provides comprehensive control capabilities in maintaining setpoints, deciding and changing setpoints, and in fault detection, diagnosis, and remediation. As pharmaceutical manufacturing moves towards continuous manufacturing from batch methods, an RTPM system would be a critical component to achieving product quality specifications. In this work, an RTPM system is presented. The RTPM system also makes use of an ontological knowledge management system called TOPS (The Ontologies for Particulate Systems). We show the uses of our TOPS-RTPM integrated system for a pharmaceutical manufacturing pilot plant that makes tablets.

Dropwise additive manufacturing of pharmaceutical products for amorphous and self emulsifying drug delivery systems

The improvements in healthcare systems and the advent of the precision medicine initiative have created the need to develop more innovative manufacturing methods for the delivery and production of individualized dosing and personalized treatments. In accordance with the changes observed in healthcare systems towards more innovative therapies, this paper presents dropwise additive manufacturing of pharmaceutical products (DAMPP) for small scale, distributed manufacturing of individualized dosing as an alternative to conventional manufacturing methods A dropwise additive manufacturing process for amorphous and self-emulsifying drug delivery systems is reported, which utilizes drop-on-demand printing technology for automated and controlled deposition of melt-based formulations onto inert tablets. The advantages of drop on demand technology include reproducible production of droplets with adjustable sizing and high placement accuracy, which enable production of individualized dosing even for low dose and high potency drugs. Flexible use of different formulations, such as lipid-based formulations, allows enhancement of the solubility of poorly water soluble and highly lipophilic drugs with DAMPP. Here, DAMPP is used to produce solid oral dosage forms from melts of an active pharmaceutical ingredient and a surfactant. The dosage forms are analyzed to show the amorphous nature, self-emulsifying drug delivery system characteristics and dissolution behavior of these formulations.

A Novel Knowledge Management System Based on Workflows

Abstract A large quantity of data, information, and knowledge are generated and accessed over the life cycle of a chemical product, from molecule discovery to process development to scale-up and production. Organizing this knowledge and making it available to support decisions has been a challenge due to its quantity, complexity, and the hierarchical data usage structure. This paper presents the functionality and technical details of a workflow-based knowledge management system and demonstrates its use in supporting the operation of a pilot plant for manufacturing liquid-based drug products.

Application of a Knowledge Management System to a Dropwise Additive Manufacturing System for Pharmaceuticals

Abstract The Knowledge Provenance Management System, KProMS captures the complete provenance of knowledge of a structured activity by modeling the details of the associated knowledge generation steps of that activity as workflows. Its unique workflow representation captures relationships between the processing steps and material and information flows, and data input and output. In this paper, we demonstrate the use of KProMS to manage and analyze experimental data for an innovative test bed for manufacturing drug products using drop-wise additive manufacturing. The drop-wise additive manufacturing system (DAMPP) uses drop-on-demand printing technology for depositing various drug formulations onto edible substrates. DAMPP requires and generates a range of data types, including camera and IR images, spectra and numerical parameter values, both of real time and off-line nature and thus serves as rich illustration of KProMS capabilities to serve as knowledge management framework.

RNEDE: Resilient network design environment

Modern living is more and more dependent on the intricate web of critical infrastructure systems. The failure or damage of such systems can cause huge disruptions. Traditional design of this web of critical infrastructure systems was based on the principles of functionality and reliability. However, it is increasingly being realized that such design objectives are not sufficient. Threats, disruptions and faults often compromise the network, taking away the benefits of an efficient and reliable design. Thus, traditional network design parameters must be combined with self-healing mechanisms to obtain a resilient design of the network. In this paper, we present RNEDE a resilient network design environment that not only optimizes the network for performance but tolerates fluctuations in its structure that result from external threats and disruptions. The environment evaluates a set of remedial actions to bring a compromised network to an optimal level of functionality. The environment includes a visualizer that enables the network administrator to be aware of the current state of the network and the suggested remedial actions at all times.