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Freeze-drying process design by manometric temperature measurement: design of a smart freeze-dryer.

PURPOSE: To develop a procedure based on manometric temperature measurement (MTM) and an expert system for good practices in freeze drying that will allow development of an optimized freeze-drying process during a single laboratory freeze-drying experiment. METHODS: Freeze drying was performed with a FTS Dura-Stop/Dura-Top freeze dryer with the manometric temperature measurement software installed. Five percent solutions of glycine, sucrose, or mannitol with 2 ml to 4 ml fill in 5 ml vials were used, with all vials loaded on one shelf. Details of freezing, optimization of chamber pressure, target product temperature, and some aspects of secondary drying are determined by the expert system algorithms. MTM measurements were used to select the optimum shelf temperature, to determine drying end points, and to evaluate residual moisture content in real-time. MTM measurements were made at 1 hour or half-hour intervals during primary drying and secondary drying, with a data collection frequency of 4 points per second. The improved MTM equations were fit to pressure-time data generated by the MTM procedure using Microcal Origin software to obtain product temperature and dry layer resistance. Using heat and mass transfer theory, the MTM results were used to evaluate mass and heat transfer rates and to estimate the shelf temperature required to maintain the target product temperature. RESULTS: MTM product dry layer resistance is accurate until about two-thirds of total primary drying time is over, and the MTM product temperature is normally accurate almost to the end of primary drying provided that effective thermal shielding is used in the freeze-drying process. The primary drying times can be accurately estimated from mass transfer rates calculated very early in the run, and we find the target product temperature can be achieved and maintained with only a few adjustments of shelf temperature. The freeze-dryer overload conditions can be estimated by calculation of heat/mass flow at the target product temperature. It was found that the MTM results serve as an excellent indicator of the end point of primary drying. Further, we find that the rate of water desorption during secondary drying may be accurately measured by a variation of the basic MTM procedure. Thus, both the end point of secondary drying and real-time residual moisture may be obtained during secondary drying. CONCLUSIONS: Manometric temperature measurement and the expert system for good practices in freeze drying does allow development of an optimized freeze-drying process during a single laboratory freeze-drying experiment.

Freeze Drying↗

Rational design of purification processes for recombinant proteins.

Recent developments in the rational design of purification processes for recombinant proteins are discussed. A review of the main issues involved in process design for protein separation and purification is presented with particular emphasis on the challenges posed by recombinant proteins. This includes physicochemical characterization of target protein and main contaminants, the use of rigorous mathematical modeling and process simulation as well as the development of an expert system and the application of this technology for optimization and design of large scale processes. An expert system for selection of optimal protein separation sequences will give the user a number of alternatives chosen on the basis of extensive data back-up on proteins and unit operations.

Biotechnology↗

Using the ID3 algorithm to find discrepant diagnoses from laboratory databases of thyroid patients.

Rare cases are a central problem when an expert system is constructed from example cases with machine learning techniques. It is difficult to make a decision support system (DSS) to cover all possible clinical cases. An inductive learning program can be used to construct an expert system for detecting cases that differ from routine cases. The ID3 algorithm and the pessimistic pruning algorithm were tested in this study: a DSS was built directly from the data of patient records. A decision tree was generated, and the cases misclassified by the decision tree as compared with the classifications of a clinician were listed on a checklist, which formed the feedback to the clinician. In clinical situations about 5-10% of functional thyroid disorders may be misclassified. At this error level, the method found over 90% of the errors with a specificity of 95%. In simple medical classification tasks this dynamic self-learning system can be used to create a DSS that can assist in the quality control of clinical decision making.

Adult↗

[New approaches to computer-assisted diagnosis of rheumatologic diseases].

UNLABELLED: Since the 1960s, several knowledge-based systems for computer-assisted diagnosis in radiology have been developed. The great majority of these tools has been implemented as off-line systems. This requires interaction with the system solely for the purpose of consultation and therefore interrupts the radiologist's work flow. This and inadequate man-machine interfaces may have inhibited the routine clinical use of such systems. The goal of this paper is to describe the current research toward the development of the on-line expert system Cadiag-4/Rheuma-Radio. The underlying fundamentals of the system design, including client/server architecture, communication interfaces, and fuzzy set theory and fuzzy logic as methods for knowledge representation and interference, are presented. METHODS: In radiology today, computers are routinely used to acquire radiological images in hospital and radiology information systems (HIS/RIS) and picture archiving and communication systems (PACS). In our approach, we make use of pre-existent sources of information to build an expert system that minimizes the interaction between radiologists and the computer. To handle uncertainty and vagueness of medical knowledge, fuzzy set theory and fuzzy logic are used. Given data of a specific case, a deductive inference procedure combines the observed radiological signs, establishes confirmed and excluded diagnoses as well as diagnostic hypotheses, and provides explanations for these conclusions. Furthermore, proposals for confirmation or exclusion of diagnostic hypotheses are offered. RESULTS: For evaluation purposes, an early prototype of Cadiag-4/Rheuma-Radio was tested on radiological disorders of the hip joint related to rheumatological diseases. Twenty radiological cases were used as test cases, reaching a diagnostic accuracy of about 80%. CONCLUSION: The first results are acceptable and encourage further work to cover the whole area of rheumatologically relevant radiological signs and diagnoses. Furthermore, research into the development of user-oriented data acquisition tools will be carried out.

Arthritis, Rheumatoid↗

A knowledge-based information system for monitoring drug levels.

The expert system shell SMR has been enhanced to include information system routines for designing data screens and providing facilities for data entry, storage, retrieval, queries and descriptive statistics. The data for inference making is abstracted from the data base record and inserted into a data array to which the knowledge base is applied to derive the appropriate advice and comments. The enhanced system has been used to develop an intelligent information system for monitoring serum drug levels which includes evaluation of temporal changes and production of specialized printed reports. The module for digoxin has been fully developed and validated. To demonstrate the extension to other drugs a module for phenytoin was constructed with only a rudimentary knowledge base. Data from the request forms together with the S-digoxin results are entered into the data base by the department secretary. The day's results are then reviewed by the clinical pharmacologist. For each case, previous results may be displayed and are taken into account by the system in the decision process. The knowledge base is applied to the data to formulate an evaluative comment on the report returned to the requestor. The report includes a semi-graphic presentation of the current and previous results and either the system's interpretation or one entered by the pharmacologist if he does not agree with it. The pharmacologist's comment is also recorded in the data base for future retrieval, analysis and possible updating of the knowledge base. The system is now undergoing testing and evaluation under routine operations in the clinical pharmacology service. It is a prototype for other applications in both laboratory and clinical medicine currently under development at Uppsala University Hospital. This system may thus provide a vehicle for a more intensive penetration of knowledge-based systems in practical medical applications.

Data Interpretation, Statistical↗

LIED--liver: information, education and diagnosis.

In this paper we describe LIED (Liver: Information, Education and Diagnosis), a diagnostic expert system devoted to medical education in the field of hepatology. LIED combines the facilities of a traditional expert system for clinical diagnosis with several modules designed for educational purposes. The goal of such modules is to train physicians, in particular as regards the improvement of their problem solving ability (at the end of their curricula students in medicine usually lack experience in organizing an efficient and accurate diagnostic process). Training on real and simulated cases has been widely recognized as a proper approach to clinical experience. The architecture of the diagnostic system is introduced, which forms the core of LIED, and which has been derived from our previous experience, and the various educational functions are discussed that were developed on top of the basic architecture.

Computer Simulation↗

Fuzzy reasoning system for fault diagnosis of physiological activities in a cultivating process.

Aiming at development of a system which supports cultivating operations, a method to diagnose physiological activities in a cultivating process is presented, and a fuzzy expert system for diagnosing Lactobacillus casei cultivating process is implemented in this paper. This system can calculate specific rates of cell growth, substrate consumption, and product formation with measuring cell mass concentration, substrate concentration, and product concentration by using a turbidity sensor and HPLC. A database is implemented, where standard curves on specific rates representing characteristics of microorganisms are stored according to normalized substrate consumption. Comparing the calculated specific rates with standard values derived from the database, the system diagnoses physiological activities of the microorganisms. As a case study, a knowledge base for diagnosing lactic acid production process is implemented. The use of fault diagnosis on pH malfunctions by the expert system proves its reasonable performance.

Biotechnology↗

Parameters for a knowledge base for acute appendicitis.

Acute appendicitis is the most common cause of acute abdomen requiring surgical intervention. The clinical diagnosis of acute appendicitis is not always easy due to variable symptomatology, particularly at the onset. The contributions of history-taking and physical examination in the diagnosis of acute appendicitis was studied in connection with the Research Committee of the World Organization of Gastroenterology (OMGE) survey of acute abdominal pain. Especially the suitability of diagnostic parameters in the construction of an expert system for automatic decision making was studied. The results clearly show that it is possible to construct an expert system for automatic decision making in the diagnosis of acute appendicitis.

Abdomen, Acute↗

Variable prediction of antiretroviral treatment outcome by different systems for interpreting genotypic human immunodeficiency virus type 1 drug resistance.

To determine the variability of genotypic human immunodeficiency virus (HIV) type 1 drug-resistance interpretation by available expert systems and its clinical implications, 261 subjects for whom a potent antiretroviral regimen was failing who were starting salvage therapy were evaluated. The association of the genotypic susceptibility score (GSS) of the salvage regimen, according to 11 interpretation systems, with HIV RNA outcomes for 6 months was examined. GSS was highly variable, as determined by the different interpretation systems, and showed independent correlation with changes from baseline HIV RNA levels at 6 months with 5 systems--Stanford hivdb, GuideLines 3.0, Retrogram 1.4, HIVresistanceWeb, and São Paulo University. Most GSSs predicted virologic response in regimens containing stavudine, lamivudine, efavirenz, or indinavir. Selected systems predicted response in regimens containing didanosine, abacavir, or nelfinavir, and no system predicted outcome of boosted protease inhibitors. GSSs predicted changes in HIV RNA levels better in adherent patients than in nonadherent individuals. Interpretation may be improved, and knowledge should be used uniformly throughout different expert systems.

Adolescent↗

Use of an expert model to test diagnostic criteria in CHARGE syndrome.

AI/GEN is an expert model of the diagnosis of deaf-blind syndromes that uses the EXPERT system developed by Rutgers University. Its knowledge structure employs criteria tables for diagnosis of the three types of CHARGE syndrome. The system has been used to test the published diagnostic criteria against the revised expert criteria, the latter being significantly more accurate than the former. The two sets of criteria are also compared with respect to the specificity and sensitivity of diagnosis. Expert systems can be of direct use to experts in refining and revising their diagnostic criteria.

Abnormalities, Multiple↗

Knowledge-based fuzzy system for diagnosis and control of an integrated biological wastewater treatment process.

A supervisory expert system based on fuzzy logic rules was developed for diagnosis and control of a laboratory- scale plant comprising anaerobic digestion and anoxic/aerobic modules for combined high rate biological N and C removal. The design and implementation of a computational environment in LabVIEW for data acquisition, plant operation and distributed equipment control is described. A step increase in ammonia concentration from 20 to 60 mg N/L was applied during a trial period of 73 h. Recycle flow rate from the aerobic to the anoxic module and bypass flow rate from the influent directly to the anoxic reactor were the output variables of the fuzzy system. They were automatically changed (from 34 to 111 L/day and from 8 to 13 L/day, respectively), when new plant conditions were recognised by the expert system. Denitrification efficiency higher than 85% was achieved 30 h after the disturbance and 15 h after the system response at an HRT as low as 1.5 h. Nitrification efficiency gradually increased from 12 to 50% at an HRT of 3 h. The system proved to react properly in order to set adequate operating conditions that led to timely and efficient recovery of N and C removal rates.

Ammonia↗

Computer-assisted diagnosis of pediatric rheumatic diseases.

OBJECTIVE: AI/RHEUM is a multimedia expert system developed originally to assist in the diagnosis of rheumatic diseases in adults. In the present study we evaluated the usefulness of a modified version of this diagnostic decision support system in diagnosing childhood rheumatic diseases. METHODOLOGY: AI/RHEUM was modified by the addition of 5 new diseases to the knowledge base of the system. Criteria tables for each of the diseases included in the knowledge base were modified to suit the needs of children. The modified system was tested on 94 consecutive children seen in a pediatric rheumatology clinic. RESULTS: AI/RHEUM made the correct diagnosis in 92% of the cases when the diagnosis was available in the knowledge base of the system. It was also shown to be effective in the education of pediatric trainees through its multimedia features. CONCLUSIONS: AI/RHEUM is an expert system that may be helpful to the nonspecialist as a diagnostic decision support system and as an educational tool.

Child↗

An epidemiologic approach to computerized medical diagnosis--AEDMI program.

A program called "An Epidemiological Approach to Computerized Medical Diagnosis" (AEDMI) is presented. Using an interactive questionnaire, physician-patient interviews are conducted and a summary of the relevant clinical data is provided. Standard items, obtained on a multi-centre basis, form a large-scale data base. Simultaneously, the reasoning of clinical experts in each real case is analyzed to obtain a knowledge-rules data base. The methodology of the program combines Bayesian systems, expert systems, and other new lines of research such as neural networks or case-based reasoning. The general concepts of clinical decision making aid systems are reviewed. This publication is aimed at obtaining international cooperation.

Artificial Intelligence↗

Development of structure-activity relationship rules for predicting carcinogenic potential of chemicals.

Since the inception of Section 5 (Premanufacturing/Premarketing Notification, PMN) of the Toxic Substances Control Act (TSCA), structure-activity relationship (SAR) analysis has been effectively used by U.S. Environmental Protection Agency's (EPA) Structure Activity Team (SAT) in the assessment of potential carcinogenic hazard of new chemicals for which test data are not available. To capture, systematize and codify the Agency's predictive expertise in order to make it more widely available to assessors outside the TSCA program, a cooperative project was initiated to develop a knowledge rule-based expert system to mimic the thinking and reasoning of the SAT. In this communication, we describe the overall structure of this expert system, discuss the scientific bases and principles of SAR analysis of chemical carcinogens used in the development of SAR knowledge rules, and delineate the major factors/rules useful for assessing the carcinogenic potential of fibers, polymers, metals/metalloids and several major classes of organic chemicals. An integrative approach using available short-term predictive tests and non-cancer toxicological data to supplement SAR analysis has also been described.

Animals↗

Toxopert-I: knowledge-based automatic interpretation of serological tests for toxoplasmosis.

Primary infection with Toxoplasma gondii, a parasite found in most regions of the world, is asymptomatic in more than 80% of cases. However, primary infection with Toxoplasma gondii in a pregnant woman might cause fetal infection and severe damage. Most cases do not require treatment. This applies to women without any infection (denoted as seronegative) and women who have acquired the infection before conception (denoted as latent). In contrast, women with postconceptual infection require immediate treatment to prevent or ameliorate fetal infection. We have developed an expert system, called Toxoport-I, designed for routine laboratory work, which automatically interprets serological test results of toxoplasma infection. By using the system the clinician can also examine questionable cases by interactively exploring possible results. We used a popular method of designing expert systems applied to medical interpretation and therapy advice, the rule-based one. In order to meet the requirements of automatic interpretation in toxoplasma serology the following characteristics were introduced: the interpretation of sequences of test results, the possibility of excluding inconsistent test results and the adaptability of the knowledge base. A decision graph that covers the different kinds of infections as well as therapy and recommendations for further tests was designed, implemented and was clinically tested by carrying out a retrospective study including 1000 pregnant women. A comparison of Toxoport-I and the clinician's interpretations yielded sensitivity and specificity rates of over 99% each.

Animals↗

Stepwise quantitative risk assessment as a tool for characterization of microbiological food safety.

This paper describes a system for the microbiological quantitative risk assessment for food products and their production processes. The system applies a stepwise risk assessment, allowing the main problems to be addressed before focusing on less important problems. First, risks are assessed broadly, using order of magnitude estimates. Characteristic numbers are used to quantitatively characterize microbial behaviour during the production process. These numbers help to highlight the major risk-determining phenomena, and to find negligible aspects. Second, the risk-determining phenomena are studied in more detail. Both general and/or specific models can be used for this and varying situations can be simulated to quantitatively describe the risk-determining phenomena. Third, even more detailed studies can be performed where necessary, for instance by using stochastic variables. The system for quantitative risk assessment has been implemented as a decision supporting expert system called SIEFE: Stepwise and Interactive Evaluation of Food safety by an Expert System. SIEFE performs bacterial risk assessments in a structured manner, using various information sources. Because all steps are transparent, every step can easily be scrutinized. In the current study the effectiveness of SIEFE is shown for a cheese spread. With this product, quantitative data concerning the major risk-determining factors were not completely available to carry out a full detailed assessment. However, this did not necessarily hamper adequate risk estimation. Using ranges of values instead helped identifying the quantitatively most important parameters and the magnitude of their impact. This example shows that SIEFE provides quantitative insights into production processes and their risk-determining factors to both risk assessors and decision makers, and highlights critical gaps in knowledge.

Cheese↗

An alternative strategy to the use of guinea pigs for the identification of skin sensitization hazard.

For over half a century, guinea pig methods have dominated the field of toxicology concerned with the identification of skin sensitizers. Specific protocols, for example the guinea pig maximization test (GPMT), have been pre-eminent in the identification of skin sensitization hazard for regulatory purposes. However, there are increasingly several forces driving change, not least animal use/welfare considerations. In response to this and to address the need for a rapid screen for chemical allergens, an alternative strategy has been developed. In the first instance, a chemical is assessed by a computer-based expert system. This system is constructed from some 50 rules describing the key chemically reactive substructures of known skin sensitizers. The output from the expert system is also evaluated in the light of the understanding of the skin penetration characteristics of the chemical. In this way, and without use of animals, the likelihood that a chemical represents a skin sensitization hazard is assessed based on the two key characteristics of a skin sensitizer: (1) its direct or indirect ability to react with skin protein (i.e. does it contain a structural alert?); and (2) the ability of the chemical to partition into the appropriate epidermal compartment. When the chemical does possess a structural alert and has the capacity to penetrate skin sufficiently, then it may be regarded as a potential skin sensitizer. Subsequent to this screening phase, if necessary the chemical may be assessed in the murine local lymph node assay. This assay is quicker and cheaper than traditional guinea pig assays and importantly is less stressful to the fewer animals that it requires. The assay is well validated and produces objective results which are equivalent to the GPMT in terms of identifying significant skin sensitization hazard. In this paper, the above strategy is described in more detail, focusing on its relevance to hazard identification and its value in animal welfare terms. It is concluded that the strategy provides an important opportunity for both substantial reduction and refinement of animal use in a manner which will not compromise the existing standard of classification and labelling of skin sensitization hazard in the European Union.

Animal Testing Alternatives↗

Reusable influence diagrams.

Influence Diagrams have been recognized as a suitable formalism for building probabilistic expert systems. Nevertheless, the most part of applications consists in stand-alone systems, concerning a very limited domain. On the other hand, Artificial Intelligence research has outlined Blackboard Architectures as the basis for building expert systems in which several knowledge sources, in general built with different formalisms, cooperate to the solution of a complex task. This paper addresses the use of influence diagrams as knowledge sources of such a system, and particularly faces the problem of reusing the same influence diagram in different inference phases. We will show that, specially in planning tasks, the modularity requirement of keeping the knowledge sources separated, may imply that an influence diagram must call another influence diagram to solve itself and to maintain the coherence of the whole set of decisions underlying the plan. Conditions for the correctness of this concatenation of knowledge sources will be provided, and an example from the medical domain of therapy planning for Acute Myeloid Leukemia will be shown, as an implemented prototype exploiting these ideas.

Acute Disease↗