Leaelaf Hailemariam

Ontological informatics infrastructure for pharmaceutical product development and manufacturing

Informatics infrastructure plays a crucial role in supporting different decision making activities related to pharmaceutical product development, pilot plant and commercial scale manufacturing by streamlining information gathering, data integration, model development and managing all these for easy and timely access and reuse. The foundation of such an infrastructure is the explicitly and formally modeled information. This foundation enables knowledge in different forms, and best manufacturing practices, to be modeled and captured into tools to support the product lifecycle management. This paper discusses the development of ontologies, Semantic Web infrastructure and Web related technologies that make such an infrastructure development possible. While many of the issues addressed in this paper are applicable to a wide spectrum of molecular-based products, we focus our work on the development of pharmaceutical informatics to support Active Pharmaceutical Ingredient (API) as well as drug product development as case studies to illustrate the various aspects of this infrastructure.

Toward intelligent decision support for pharmaceutical product development

Developing pharmaceutical product formulation in a timely manner and ensuring quality is a complex process that requires a systematic, science-based approach. Information from various categories, including properties of the drug substance and excipients, interactions between materials, unit operations, and equipment is gathered. Knowledge in different forms, including heuristics, decision trees, correlations, and first-principle models is applied. Decisions regarding processing routes, choice of excipients, and equipment sizing are made based on this information and knowledge. In this work, we report on the development of a software infrastructure to assist formulation scientists in managing the information, capturing the knowledge, and providing intelligent decision support for pharmaceutical product formulation.

Onto MODEL: Ontological mathematical modeling knowledge management

Abstract In this paper we describe OntoMODEL, an ontological mathematical model management tool that facilitates systematic, standardizable methods for model storage, use and solving. While the declarative knowledge in mathematical models has been captured using ontologies, the procedural knowledge required for solving these models has been handled by commercially available scientific computing software such as Mathematica and an execution engine written in Java. The interactions involved are well established and the approach is intuitive, therefore not requiring model user familiarity with any particular programming language or modeling software. Apart from this key benefit, the fact that OntoMODEL lends itself to more advanced applications such as model based fault diagnosis, model predictive control, process optimization, knowledge based decision making and process flowsheet simulation makes it an in dispensable tool in the intelligent automation of process operations. This paper also discusses the shortcomings of existing approaches that OntoMODEL addresses and also details its framework and use.

Excipient interaction prediction: application of the Purdue Ontology for Pharmaceutical Engineering (POPE)

Abstract A drug product consists of a drug substance and one or more excipients that play specific roles in rendering desired properties to that product, from improvement of flow to control of the release of the drug substance. Inter-excipient and drug substance-excipient chemical reactions are to be avoided and formulators often use heuristics and past experience to avoid potential interactions during drug product development. Multiple tools are present to mechanistically predict chemical reactions: however their utility is limited due to the complexity of the domain and the need for explicit information. In this work, the Purdue Ontology for Pharmaceutical Engineering (POPE) was used to develop an excipient reaction prediction application that made use of structural, material and environmental information to predict reactions

A unified approach for knowledge modeling in pharmaceutical product development

Abstract Development of a drug product is a complex, iterative process consisting of selection of a dosage form, excipients, processing route, operating equipment and so on. At each stage, knowledge in various forms, including heuristics, decision trees and mathematical models, is used in making decisions. Typically knowledge is modeled specifically for the tool that uses it, such as expert systems and mathematical modeling software. This makes it very difficult to share the knowledge, across different tools and among development teams, and integrate various forms of knowledge to assist in making pharmaceutical product development decisions. To provide easier access to available knowledge and better decision support, we propose an, open and unified approach to systematically model the different forms of knowledge.

Information modeling for pharmaceutical product development

Abstract Development of a pharmaceutical product involves several inter-related steps with multiple decisions requiring iterative improvements. Large amounts of information, including the properties of a drug substance, interactions of materials, unit operations, equipment etc, have to be gathered and used for decision making. A systematic model of the associated information is thus needed to streamline the product development process and provide a common foundation to support the information. Following the information-centric infrastructure proposed in our earlier work, ontology has been used to model the information. The information modeled as ontology provides information in a way that can be easily used by humans and processed by machines. The information modeling process and developed ontology are discussed in detail. The benefits are demonstrated by using a case study for managing information generated from the preformulation stage of pharmaceutical product development.