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At least 271 records · Page 15Linked to original sources

PubMed2005

Dynamic collimator optimization compared with fixed collimator angle in arc-based stereotactic radiotherapy: a dosimetric analysis.

OBJECT: The purpose of this study was to determine the effect of static and dynamic collimator optimization when using a micromultileaf collimator (mMLC) in dynamic-arc stereotactic radiosurgery (SRS) by evaluating the dose to healthy peritumoral tissue. METHODS: Thirty patients previously treated for intracranial lesions with the BrainLAB mMLC underwent retrospective replanning. Three collimator optimization strategies were compared for a simulated SRS treatment plan, as follows: Strategy 1, static collimation fixed at 90 degrees throughout arcs; Strategy 2, static collimator settings optimized for each arc; and Strategy 3, dynamic collimator settings optimized every 10 degrees throughout treatment arcs. Dose-volume histograms for a 0.7-cm shell of healthy peritumoral tissue were quantitatively compared. Collimator optimization schemes (Strategies 2 and 3) significantly decreased the volume of peritumoral tissue that is irradiated when compared with static collimation at 90 degrees (Strategy 1). The volume was reduced by 40.6% for Strategy 2 (95% confidence interval [CI] +/- 11) and by 47.1% for Strategy 3 (95% CI +/- 8.1) at the 95% isodose; by 28.4% for Strategy 2 (95% CI +/- 4.9) and 39.1% for Strategy 3 (95% CI +/- 6) at the 90% isodose; and by 18.2% for Strategy 2 (95% CI +/- 8.1) and 25.4% for Strategy 3 (95% CI +/- 7.1) at the 80% isodose. Serial collimator optimization throughout the treatment arcs (Strategy 3) reduced the mean volume of peritumoral tissue irradiated when compared with static collimator optimization (Strategy 2), by 16.1% (95% CI +/- 1.5) at 95% isodose, by 11.7% (95% CI +/- 1) at 90% isodose, and by 8.2% (95% CI +/- 1.2) at 80% isodose regions. In specific cases, linear or polynomial functions were formulated to optimize collimator settings dynamically throughout treatment arcs. CONCLUSIONS: Dynamic collimator optimization during arc-based SRS decreases the volume of healthy peritumoral tissue treated with high doses of radiation and appears to be an effective method of improving target conformality. This study is the first step toward determination of a smoothing function algorithm to allow for true dynamic collimation during SRS.

Brain Neoplasms↗

PubMed2003

On the generality of optimal versus objective classifier feedback effects on decision criterion learning in perceptual categorization.

Biased category payoff matrices engender separate reward- and accuracy-maximizing decision criteria Although instructed to maximize reward, observers use suboptimal decision criteria that place greater emphasis on accuracy than is optimal. In this study, objective classifier feedback (the objectively correct response) was compared with optimal classifier feedback (the optimal classifier's response) at two levels of category discriminability when zero or negative costs accompanied incorrect responses for two payoff matrix multiplication factors. Performance was superior for optimal classifier feedback relative to objective classifier feedback for both zero- and negative-cost conditions, especially when category discriminability was low, but the magnitude of the optimal classifier advantage was approximately equal for zero- and negative-cost conditions. The optimal classifier feedback performance advantage did not interact with the payoff matrix multiplication factor. Model-based analyses suggested that the weight placed on accuracy was reduced for optimal classifier feedback relative to objective classifier feedback and for high category discriminability relative to low category discriminability. In addition, the weight placed on accuracy declined with training when feedback was based on the optimal classifier and remained relatively stable when feedback was based on the objective classifier. These results suggest that feedback based on the optimal classifier leads to superior decision criterion learning across a wide range of experimental conditions.

Decision Making↗

PubMedDate not supplied

Performance of the OptiMAL assay for detection and identification of malaria infections in asymptomatic residents of Irian Jaya, Indonesia.

The OptiMAL assay, a new immunochromatographic "dipstick" test for malaria based on detection of Plasmodium lactate dehydrogenase (pLDH), is purported to detect infections of approximately 200 parasites/microL of blood and to differentiate between Plasmodium falciparum and non-P. falciparum. We evaluated OptiMAL performance by comparing the test strip interpretations of two independent readers with consensus results obtained independently by expert malaria microscopists. Unbiased measures of sensitivity were derived by applying the OptiMAL test for detection and differentiation of light, asymptomatic infections by P. falciparum and Plasmodium vivax. OptiMAL readings were separated in time to determine whether the reaction signal was stable. Microscopy identified infections in 225 of 505 individuals screened; those with P. falciparum (n = 170) averaged 354 asexual forms/microL and P. vivax/Plasmodium malariae (n = 112) averaged 216 asexual forms/microL of blood. Concordance between OptiMAL and microscopy was 81% and 78% by the two independent readings. The assay's sensitivity for detection of any malaria species was 60.4% and 70.2% respectively and specificity was 97% and 89%. Most cases identified by microscopy as P. falciparum were graded as negative or non-falciparum by both OptiMAL readers. OptiMAL false negatives as well as misidentifications were related to low parasitemias (< 500/microL). The OptiMAL assay demonstrated 88-92% sensitivity for detecting infections of 500-1,000 parasites/microL, a range covering the mean parasitemia of primary symptomatic P. falciparum infections in malaria-naïve Indonesian transmigrants. This device was markedly less sensitive than expert microscopy for discriminating between malaria species and is presently unsuited for use as an epidemiological screening tool. The OptiMAL assay is not approved for diagnostic use but is commercially available for research purposes only.

Animals↗

PubMed2001

[Culture medium optimization and primary kinetics analysis for nisin production].

Response surface methodology was used to optimize a medium for nisin production of Lactococcus lactis. In the first optimization step the influence of sucrose, soybean peptone, yeast extract, potassium dihydrogen phosphate, sodium chloride, and magnesium sulfur on nisin production was evaluated using a fractional factorial design. Potassium dihydrogen phosphate influenced nisin production positively while soybean peptone affected nisin production negatively. The other components had no significant effect on nisin production. The path of steepest ascent was used to approach the optimal region of the medium composition. In the third step the optimal concentrations of KH2PO4 and soybean peptone were determined by a central composite design and response surface analysis. The optimized medium allowed nisin production to be increased from 1074 IU/mL to 2150 IU/mL. The kinetic analysis showed that nisin production fashion at optimized and non-optimized media was not changed and maintained partially growth-associated. But the specific growth rates and the specific nisin production rates for the strain at the optimized medium were bigger than the ones at the non-optimized medium after the cells entered the middle of exponential phase.

Anti-Bacterial Agents↗

PubMed1996

Optimal sample allocation in clinical trials designed to investigate relative risks.

Clinical trials with more than two groups are becoming increasingly common, especially trials with both active and placebo control groups. Equal allocation of subjects to each of the groups is the most common sample allocation, but in clinical trials where the purpose is to test hypotheses of relative risk, such as vaccine trials, equal allocation can be substantially sub-optimal. Optimal allocation for clinical trials has been considered previously, but not for trials with more than two groups. In this paper optimal sample allocation for relative risk trials is investigated in a variety of situations. The main results are as follows: (i) there are many situations where reductions of more than 20 per cent in sample size can be obtained by using optimal allocation instead of equal allocation; (ii) the optimal allocation for two group studies is not optimal in general; (iii) in many situations optimal allocation increases a subject's chances of being enrolled to a test treatment, and (iv) in most cases a grid search using the likelihood score asymptotic power function is the easiest method of finding an approximately optimal allocation. Extensions to situations more general than those covered here are sketched.

Case-Control Studies↗

PubMed2004

Perioperative fluid volume optimization following proximal femoral fracture.

BACKGROUND: Proximal Femoral Fracture (PFF) or 'hip fracture' is a frequent injury, and adverse outcomes are common. Several factors suggest the importance of developing techniques to optimize intravascular fluid volume. These may include protocols that enhance the efficacy of clinicians' assessments, invasive techniques such as oesophageal Doppler or central venous pressure monitoring, or advanced non-invasive techniques such as plethysmographic pulse volume determination. OBJECTIVES: To determine the optimal method of fluid volume optimization for adult patients undergoing surgical repair of PFF. Comparisons of fluid types, of blood transfusion strategies or of pharmacological interventions are not considered in this review. SEARCH STRATEGY: We searched CENTRAL (The Cochrane Library, issue 4, 2003), MEDLINE (1985 to 2003), EMBASE (1985 to 2003), and bibliographies of retrieved articles. Relevant journals and conference proceedings were handsearched. SELECTION CRITERIA: Randomized controlled studies comparing a fluid optimization intervention with normal practice or with another fluid optimization intervention, in patients following PFF undergoing surgery of any type under anaesthesia of any type. DATA COLLECTION AND ANALYSIS: Searches and exclusion of clearly irrelevant articles were performed by one reviewer. Two reviewers examined independently the remaining studies, extracting study quality and results data. A wide range of short- and long-term outcome data were sought. Studies were excluded if they did not meet selection criteria or if results were likely to be biased. Due to inconsistent data reporting, combination of data was not generally possible. MAIN RESULTS: Searches identified four trials, of which two studies, randomizing a total of 130 patients, were of adequate quality and addressed the review question. Both studies were of invasive advanced haemodynamic monitoring, either oesophageal Doppler ultrasonography or central venous pressure monitoring, during the intraoperative period only. In both, invasive monitoring led to significant increases in fluid volumes infused and reductions in length of hospital stay. The pooled Peto odds ratio for in-hospital fatality was 1.44 (95% confidence interval 0.45-4.62). Neither study followed patients beyond hospital discharge or assessed functional outcomes. No serious complications were directly attributable to the interventions. There were no studies of protocol-guided fluid optimization or of advanced non-invasive techniques. REVIEWER'S CONCLUSIONS: Invasive methods of fluid optimization during surgery may shorten hospital stay, but their effects on other important, patient-centred, longer-term outcomes are uncertain. Adverse effects on fatality cannot be excluded. Other fluid optimization techniques have not been evaluated. The lack of randomized studies of adequate quality addressing this important question is disappointing. More research is needed.

Femoral Fractures↗

PubMed2005

Estimating optimal profiles of genetic alterations using constraint-based models.

Metabolic engineering involves application of recombinant DNA methods to manipulate metabolic networks to improve cellular properties. It is critical that the genetic alterations be performed in an optimal manner to maximize profit. In addition to the product yield, productivity consideration is also critical, especially for the production of bulk chemicals such as 1,3-propanediol. In this work, we demonstrate that it is suboptimal from the standpoint of productivity to induce genetic alteration at the start of the production process. A bi-level optimization scheme is formulated to determine the optimal temporal flux profile for the manipulated reaction. In the first case study, an optimal flux in the reaction catalyzed by glycerol kinase is determined to maximize the glycerol production at the end of a 6-h batch cultivation of Escherichia coli under aerobic conditions. The final glycerol concentration is 30% higher for the optimal flux profile compared with having an active flux during the entire batch. The effect of the mass transfer coefficient on the optimal profile and the glycerol concentration is also determined. In the second case study, the anaerobic batch fermentation of the ldh(-) strain of Escherichia coli is considered. The optimal flux in the acetate pathway is determined to maximize the final ethanol concentration. The optimal flux results in higher ethanol concentration (11.92 mmol L(-1)) compared to strains with no acetate flux (8.36 mmol L(-1)) and fully active acetate flux (6.22 mmol L(-1)). We also examine the effects of growth inhibition due to high ethanol concentrations and variations in final batch time on ethanol production.

Algorithms↗

PubMed2005

Optimization of human serum albumin production in methylotrophic yeast Pichia pastoris by repeated fed-batch fermentation.

An optimization method for repeated fed-batch fermentation was established with the aim of improving the recombinant human serum albumin (rHSA) production in Pichia pastoris. A simulation model for fed-batch fermentation was formulated and the optimal methanol-feeding policy calculated by dynamic programming method using five different methanol-feeding periods. The necessary state variables were collected from the calculated results and used for further optimization of repeated fed-batch fermentation. The optimal operation policy was investigated using the pre-collected state variables by estimating the overall profit per total methanol-feeding time. The calculated results indicated that the initial cell mass from the 2nd fed-batch fermentation on should be set at 35 or 40 g and methanol-feeding time at 264 h. In repeated fed-batch fermentation using the optimal operation policy, actual culture volume was in good agreement with the values simulated by model equations, but some discrepancy was observed in rHSA production. Minimum experiments were therefore carried out to re-evaluate rHSA production levels, which were then applied in re-calculations to determine the optimal operation policy. The optimal policy for repeated fed-batch fermentation established in the present study (i.e., 4-times-repeated fed-batch fermentation) achieved a 47% increase in annual rHSA production. Optimization of the culture period also brought about a 28% increase in annual rHSA production even in simple (not repeated) fed-batch fermentation.

Algorithms↗

PubMed2004

Estimation of an optimal radiotherapy utilization rate for gastrointestinal carcinoma: a review of the evidence.

BACKGROUND: Radiotherapy utilization rates for cancer vary widely, both within and between countries. The optimal proportion of patients with gastrointestinal malignancies who should receive at least one course of radiotherapy at some time during their illness is an important benchmark. METHODS: The authors studied treatment guidelines and treatment reviews to identify the indications for radiotherapy for patients with gastrointestinal malignancies. Optimal radiotherapy utilization trees were constructed to show the clinical attributes of patients with gastrointestinal carcinomas who will benefit from radiotherapy. Epidemiologic incidence data for each of these clinical attributes were obtained to calculate the optimal proportion of all patients with gastrointestinal malignancies for whom radiotherapy was considered appropriate. Optimal rates of radiotherapy use were compared with actual rates in population-based studies to assess any discrepancies between actual and optimal radiotherapy utilization rates. RESULTS: Radiotherapy was indicated in 80% of patients with esophageal carcinoma, 68% of patients with gastric carcinoma, 57% of patients with pancreatic carcinoma, 13% of patients with carcinoma of the gallbladder, 0% of patients with hepatic carcinoma, 14% of patients with colon carcinoma, and 61% of patients with rectal carcinoma. The actual radiotherapy utilization rates for most of these gastrointestinal malignancies fell well short of optimal rates, which were derived from evidence-based treatment guidelines. CONCLUSIONS: It is possible to model optimal radiotherapy utilization using published treatment guidelines and existing incidence data. There was a discrepancy between the optimal and actual rates of radiotherapy utilization for patients with carcinomas of the esophagus, stomach, pancreas, and rectum. Strategies to implement evidence-based clinical guidelines are recommended.

Benchmarking↗

PubMed2005

Estimation of an optimal external beam radiotherapy utilization rate for head and neck carcinoma.

BACKGROUND: Radiotherapy is used commonly in the treatment of patients with head and neck carcinoma. The benchmark radiotherapy utilization rates for head and neck carcinoma largely are unknown. The objective of the current study was to determine the optimal radiotherapy utilization rate for patients with head and neck carcinoma and to compare this optimal rate with actual utilization rates where actual utilization data were available. METHODS: An optimal radiotherapy utilization tree was constructed that depicted all patients with head and neck carcinoma in whom radiotherapy was indicated according to evidence-based treatment guidelines. The proportions of patients with clinical attributes that indicated possible benefit from radiotherapy were obtained from epidemiological data and were inserted into the utilization tree. The optimal proportion of patients with carcinoma of the head and neck who should receive radiotherapy was calculated by merging the evidence-based recommendations with the epidemiological data in the tree. Optimal rates of radiotherapy utilization were compared with actual rates obtained from population-based studies. RESULTS: Radiotherapy was indicated at some point during their illness in 74% of all patients with head and neck carcinoma. By subsite, the optimal radiotherapy utilization rates were oral cavity, 74%; lip, 20%; larynx, 100%; oropharynx, 100%; salivary gland, 87%; hypopharynx, 100%; nasopharynx, 100%; paranasal sinuses, 100%; and unknown squamous cell carcinoma of the head and neck, 90%. All treatment recommendations were based on Level III or IV evidence. Assessment of actual radiotherapy utilization rates indicated an increased use of radiotherapy over time for head and neck carcinoma. However, there also were some decreases in the use of radiotherapy for some carcinoma subsites over the past 20 years, despite the lower actual rates compared with the optimal rates. The reasons for these reductions in use were not identified. CONCLUSIONS: The actual radiotherapy utilization rate for patients with head and neck carcinoma corresponded reasonably closely to the optimal rate for some populations but also identified some shortfalls for other patient groups. The results of this study provide a way of assessing shortfalls in radiotherapy.

Benchmarking↗

PubMed2006

Estimation of the optimal brachytherapy utilization rate in the treatment of carcinoma of the uterine cervix: review of clinical practice guidelines and primary evidence.

BACKGROUND: Brachytherapy (BT) is an integral part of cervical carcinoma treatment. There have been no attempts to estimate the optimal proportion of new cervical carcinoma cases that should be treated with BT, that is, the optimal rate of brachytherapy utilization (BTU). METHODS: Evidence-based guidelines and primary evidence were used to construct a BTU tree for carcinoma of the uterine cervix. Searches were performed of the epidemiological literature to ascertain the proportion of patients who fulfilled criteria for BT. The robustness of the model was tested by sensitivity analyses and by peer review. A patterns of care study of BT in New South Wales for 2003 was conducted, and actual BTU for cervical carcinoma determined. The differences between optimal and actual rates of BTU were assessed. RESULTS: The optimal cervical carcinoma BTU was 49% (range, 42% to 50%). In New South Wales in 2003, actual BTU was only 30% of 256 cervical carcinoma patients. The major discrepancy was for FIGO stage IB-IIA disease, where there was an underutilization of BT, estimated to be 15% actual use compared with 47% optimal use. In Surveillance, Epidemiology, and End Results (SEER) areas, there was underutilization for stage IB-IIA (22% actual BTU versus 47% optimal BTU) and for stage IIB-IVA (54% actual BTU versus 100% optimal BTU). CONCLUSIONS: BT for cervical carcinoma is underutilized in New South Wales and in SEER areas. The authors' model of optimal BTU can be used as a quality assurance tool to provide an evidence-based benchmark against which actual patterns of practice can be measured. The model can also be used to help determine adequacy of BT resource allocation.

Benchmarking↗

PubMed1994

Optimization of the electrostatic interactions in proteins of different functional and folding type.

The 3-dimensional optimization of the electrostatic interactions between the charged amino acid residues was studied by Monte Carlo simulations on an extended representative set of 141 protein structures with known atomic coordinates. The proteins were classified by different functional and structural criteria, and the optimization of the electrostatic interactions was analyzed. The optimization parameters were obtained by comparison of the contribution of charge-charge interactions to the free energy of the native protein structures and for a large number of randomly distributed charge constellations obtained by the Monte Carlo technique. On the basis of the results obtained, one can conclude that the charge-charge interactions are better optimized in the enzymes than in the proteins without enzymatic functions. Proteins that belong to the mixed alpha beta folding type are electrostatically better optimized than pure alpha-helical or beta-strand structures. Proteins that are stabilized by disulfide bonds show a lower degree of electrostatic optimization. The electrostatic interactions in a native protein are effectively optimized by rejection of the conformers that lead to repulsive charge-charge interactions. Particularly, the rejection of the repulsive contacts seems to be a major goal in the protein folding process. The dependence of the optimization parameters on the choice of the potential function was tested. The majority of the potential functions gave practically identical results.

Computer Simulation↗

PubMed1977

A model of optimal voluntary muscular control.

In the absence of detailed knowledge of how the CNS controls a muscle through its motor fibers, a reasonable hypothesis is that of optimal control. This hypothesis is studied using a simplified mathematical model of a single muscle, based on A.V. Hill's equations, with series elastic element omitted, and with the motor signal represented by a single input variable. Two cost functions were used. The first was total energy expended by the muscle (work plus heat). If the load is a constant force, with no inertia, Hill's optimal velocity of shortening results. If the load includes a mass, analysis by optimal control theory shows that the motor signal to the muscle consists of three phases: (1) maximal stimulation to accelerate the mass to the optimal velocity as quickly as possible, (2) an intermediate level of stimulation to hold the velocity at its optimal value, once reached, and (3) zero stimulation, to permit the mass to slow down, as quickly as possible, to zero velocity at the specified distance shortened. If the latter distance is too small, or the mass too large, the optimal velocity is not reached, and phase (2) is absent. For lengthening, there is no optimal velocity; there are only two phases, zero stimulation followed by maximal stimulation. The second cost function was total time. The optimal control for shortening consists of only phases (1) and (3) above, and is identical to the minimal energy control whenever phase (2) is absent from the latter. Generalization of this model to include viscous loads and a series elastic element are discussed.

Biophysical Phenomena↗

PubMed2006

Optimal environmental management strategy and implementation for groundwater contamination prevention and restoration.

An innovative management strategy is proposed for optimized and integrated environmental management for regional or national groundwater contamination prevention and restoration allied with consideration of sustainable development. This management strategy accounts for availability of limited resources, human health and ecological risks from groundwater contamination, costs for groundwater protection measures, beneficial uses and values from groundwater protection, and sustainable development. Six different categories of costs are identified with regard to groundwater prevention and restoration. In addition, different environmental impacts from groundwater contamination including human health and ecological risks are individually taken into account. System optimization principles are implemented to accomplish decision-makings on the optimal resources allocations of the available resources or budgets to different existing contaminated sites and projected contamination sites for a maximal risk reduction. Established management constraints such as budget limitations under different categories of costs are satisfied at the optimal solution. A stepwise optimization process is proposed in which the first step is to select optimally a limited number of sites where remediation or prevention measures will be taken, from all the existing contaminated and projected contamination sites, based on a total regionally or nationally available budget in a certain time frame such as 10 years. Then, several optimization steps determined year-by-year optimal distributions of the available yearly budgets for those selected sites. A hypothetical case study is presented to demonstrate a practical implementation of the management strategy. Several issues pertaining to groundwater contamination exposure and risk assessments and remediation cost evaluations are briefly discussed for adequately understanding implementations of the management strategy.

Environmental Exposure↗

PubMed2004

Development of an optimal sampling strategy for clinical pharmacokinetic studies of the novel anthracycline disaccharide analogue MEN-10755.

AIM: MEN-10755 is a novel anthracycline analogue that has shown an improved therapeutic efficacy over doxorubicin in animal models, especially in gynaecological and lung cancers and is currently under clinical development for the treatment of solid tumours. The aim of the project was to develop an optimal sampling strategy for MEN-10755 to provide an efficient basis for future pharmacokinetic/pharmacodynamic investigations. METHODS: Data from 24 patients who participated in a phase I clinical pharmacokinetic study of MEN-10755 administered as a short i.v. infusion were included. Individual pharmacokinetic values were calculated by fitting the plasma concentration data to a two-compartment model using nonlinear least-squared regression (KINFIT, Ed 3.5). Population pharmacokinetic analysis was carried out using (a) the traditional standard two-stage method (STS) based on all data (KINFIT-ALL), (b) the iterative two-stage Bayesian (IT(2)B) population modelling algorithm (KINPOP), and (c) the STS method using KINFIT and using four optimally timed plasma concentrations (KINFIT-OSS4). Determinant (D) optimal sampling strategy (OSS) was used to evaluate the four most information-rich sampling times. The pharmacokinetic parameters V(c) (l), k(el) (h(-1)), k(12) (h(-1)) and k(21) (h(-1)) calculated using KINPOP served as a model for calculation of four D-optimal sampling times. D-optimal sampling data sets were analysed using KINFIT-OSS4 and compared with the population model obtained by the traditional standard two-stage approach for all data sets (KINFIT-ALL). RESULTS: The optimal sampling times were: the end of the infusion, and 1.5 h, 3.8 h and 24 h after the start of the infusion. The four-point D-optimal sampling design determined in this study gave individual parameter estimates close to the basic standard estimates using the full data set. CONCLUSION: Because accurate estimates of pharmacokinetic parameters were achieved, the four-point D-optimal sampling design may be very useful in future studies with MEN-10755.

Algorithms↗

PubMed2004

A novel model of motor learning capable of developing an optimal movement control law online from scratch.

A computational model of a learning system (LS) is described that acquires knowledge and skill necessary for optimal control of a multisegmental limb dynamics (controlled object or CO), starting from "knowing" only the dimensionality of the object's state space. It is based on an optimal control problem setup different from that of reinforcement learning. The LS solves the optimal control problem online while practicing the manipulation of CO. The system's functional architecture comprises several adaptive components, each of which incorporates a number of mapping functions approximated based on artificial neural nets. Besides the internal model of the CO's dynamics and adaptive controller that computes the control law, the LS includes a new type of internal model, the minimal cost (IM(mc)) of moving the controlled object between a pair of states. That internal model appears critical for the LS's capacity to develop an optimal movement trajectory. The IM(mc) interacts with the adaptive controller in a cooperative manner. The controller provides an initial approximation of an optimal control action, which is further optimized in real time based on the IM(mc). The IM(mc) in turn provides information for updating the controller. The LS's performance was tested on the task of center-out reaching to eight randomly selected targets with a 2DOF limb model. The LS reached an optimal level of performance in a few tens of trials. It also quickly adapted to movement perturbations produced by two different types of external force field. The results suggest that the proposed design of a self-optimized control system can serve as a basis for the modeling of motor learning that includes the formation and adaptive modification of the plan of a goal-directed movement.

Adaptation, Physiological↗

PubMed1988

DESIGN: computerized optimization of experimental design for estimating Kd and Bmax in ligand binding experiments. I. Homologous and heterologous binding to one or two classes of sites.

We have developed a versatile computer program for optimization of ligand binding experiments (e.g., radioreceptor assay system for hormones, drugs, etc.). This optimization algorithm is based on an overall measure of precision of the parameter estimates (D-optimality). The program DESIGN uses an exact mathematical model of the equilibrium ligand binding system with up to two ligands binding to any number of classes of binding sites. The program produces a minimal list of the optimal ligand concentrations for use in the binding experiment. This potentially reduces the time and cost necessary to perform a binding experiment. The program allows comparison of any proposed experimental design with the D-optimal design or with assay protocols in current use. The level of nonspecific binding is regarded as an unknown parameter of the system, along with the affinity constant (Kd) and binding capacity (Bmax). Selected parameters can be fixed at constant values and thereby excluded from the optimization algorithm. Emphasis may be placed on improving the precision of a single parameter or on improving the precision of all the parameters simultaneously. We present optimal designs for several of the more commonly used assay protocols (saturation binding with a single labeled ligand, competition or displacement curve, one or two classes of binding sites), and evaluate the robustness of these designs to changes in parameter values of the underlying models. We also derive the theoretical D-optimal design for the saturation binding experiment with a homogeneous receptor class.

Binding Sites↗

PubMed1996

Implementation of OSPOP, an algorithm for the estimation of optimal sampling times in pharmacokinetics by the ED, EID and API criteria.

The most common approach to optimize the sampling schedule in parameter estimation experiments is the D-optimality criterion, which consists in maximizing the determinant of the Fisher information matrix (max det F). In order to incorporate prior parameter uncertainty in the optimal design, other criteria have been proposed: The ED = max E (det F), EID = min E (l/det F) and API = max E (log det F) criteria, where the expectation is with respect to the given prior distribution of the parameters. Previously described algorithm for the estimation of optimal sampling times according to these criteria are adaptive random search (ARS), a robust and global but slow optimizer for API, and stochastic gradient (SG), a fast but local optimizer for ED and EID. We implemented an algorithm named OSPOP 1.0, based on non-adaptive random search (RS) followed by stochastic gradient to determine optimal sampling times for parameter estimation in various pharmacokinetic models according to ED, EID and API criteria. Prior distributions are allowed to be uniform, normal or lognormal. This algorithm combines the robustness of RS and the speediness of SG (convergence is obtained in a few minutes on a microcomputer). The results of the SG algorithm have been compared to those described in the literature using the ARS algorithm on a one compartment model with first- order absorption and were very similar. Also, the CPU time needed by SG and ARS algorithms were compared and the former proved to be much faster. Then, it has been applied to a five parameters stochastic model with zero-order absorption rate and Weibull-distributed residence times which was shown to describe adequately the kinetics of metacycline in humans. Population pharmacokinetic parameters of metacycline were estimated from a six subject pilot study, by the iterative two-staged method, using ADAPT II repeatedly. Optimal sampling times were determined with each criterion (ED, EID, API) with a multivariate normal prior parameter distribution. Six to seven distinct sampling times could be estimated. Higher numbers of samples revealed coalescing of design points.

Algorithms↗