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PubMed1996

Role of pharmacokinetic-pharmacodynamic principles in rational and cost-effective drug development.

An important goal of drug development is to define dose and concentration-response relationships for new drugs and biologics. Such critical information from controlled clinical trials can provide primary evidence of efficacy and safety and an informative database for devising dosing instructions for clinical use. This article describes applications of pharmacologic principles [pharmacokinetic-pharmacodynamic (PK-PD)] and modeling methods for drugs in which the evaluation process is guided by and/or identifies significant PK and/or PD variability in drug response. In the case of the recently registered immunosuppressive agent, tacrolimus, preclinical PK-PD in model systems can be used to rationally design safe and effective immunomodulatory dosing regimens for phase 1 clinical studies. Furthermore, a study design based on concentration control guided by a novel artificial intelligence modeling system (AIMS) can be efficiently applied to conduct randomized clinical trials in auto-immunity and to implement cost-effective therapeutic drug monitoring of tacrolimus and cyclosporine in clinical transplantation. In the case of a cardioselective beta-adrenergic blocking agent, betaxolol, marketed for essential hypertension, population PD modeling can be shown to be a more efficient method for estimating dose response compared with standard statistical tests. Using a sigmoid Emax PD model, only a fraction (40 of 300) of the randomized patients was needed to demonstrate dose response. Therefore, two methods, i.e., PD modeling of dose response and AIMS-guided dosing, can achieve significant cost benefits for drug developers, patient care, and the health care system.

Artificial Intelligence↗
PubMedDate not supplied

Drug development in India.

The drug development process is complex. It takes about 5--7 years before a compound synthesised in the laboratory can be made available the general practitioner for therapeutic usage. Furthermore, only a few of the compounds developed and synthesised in the laboratory with possible hope of therapeutic application, satisfactorily pass through all the stages of development process. Complete development of a new drug may cost 10--15 million rupees and needs the technical expertise of the highest order. Obviously this calls for tremendous financial and human resources. It is, therefore, imperative that research investments are properly planned and wisely made. It should be a well coordinated team effort with deep considerations of economic management. Clinical pharmacology plays an essential and a meaningful role in this process and its interactions with the pharmaceutical industry should be such as to ensure therapeutic efficacy and safety of new drugs.

Animals↗
PubMed1997

An evaluation of the integration of pharmacokinetic and pharmacodynamic principles in clinical drug development. Experience within Hoffmann La Roche.

The integration of pharmacokinetic and pharmacodynamic principles into drug development has been proposed as a way of making it more rational and efficient. The use of these principles in drug development to make scientific and strategic decisions is defined as the 'pharmacokinetic-pharmacodynamic guided approach to drug development'. The objectives of this survey were: (i) to assess the extent the pharmacokinetic-pharmacodynamic guided approach to drug development has been used in a large multinational pharmaceutical company: (ii) to evaluate the impact of pharmacokinetic and/or pharmacodynamic results on clinical drug development; and (iii) to identify factors which prevented the full application of the pharmacokinetic-pharmacodynamic guided approach. This was done by looking at 18 projects in the current development portfolio at Hoffman La Roche and evaluating the use of this approach by interviewing the responsible clinical pharmacologist using a standardised questionnaire. (i) Benefits from using the pharmacokinetic-pharmacodynamic guided approach were reported in every project, independent of development phase and therapeutic area. This approach was more extensively used in the recent projects. The selection of dosages in clinical studies was found to be the most important application of pharmacokinetic-pharmacodynamic results in terms of an impact on drug development. (ii) Time savings, up to several months, could be quantified in 8 projects during the entry-into-man studies and in 6 projects during the phase II or III studies. In 4 projects, 1 clinical study was avoided. (iii) The most important scientific factor preventing the full application of the approach was the lack of knowledge on the predictive value of the pharmacodynamic or surrogate marker for effect (6 projects). The results of the survey have shown that the use of the pharmacokinetic-pharmacodynamic guided approach has contributed to making clinical drug development more rational and more efficient. Opportunities to apply the pharmacokinetic-pharmacodynamic approach should be identified in each project and a project specific strategy for the pharmacokinetic-pharmacodynamic guided approach should be defined during phase 0 of drug development.

Cost-Benefit Analysis↗
PubMedDate not supplied

A forecasting approach to accelerate drug development.

The clinical phase of drug development should be concluded sooner and at a lower cost if primarily only the pivotal and supportive studies were to be conducted. Such improved efficiency requires development of a decision support system that delivers five new capabilities: (i) it enables one to predict a result of a clinical study and to identify those studies that are expected to have an acceptable probability of success; (ii) it will allow one to optimally utilize available pharmacokinetic and pharmacodynamic (PK/PD) data and improve its predictive capability as more data become available; (iii) it will enable one to project useful population results, not just mean results; (iv) predictions will be accompanied by a measure of reliability; and (v) expected initial clinical results will be predictable from animal and related drug class data. With such a tool population targets could be specified very early in the drug development programme, challenged, and then rationally revised at each step during the development process. This report describes progress in developing and testing a clinical trials Forecaster, a prototype for such a system. The Forecaster generates estimates of the joint density for a population of combined PK/PD parameters. That population then serves as a surrogate for the population of individuals. When the resulting joint density is sampled, the obtained sets of parameters may be used to generate data that is statistically indistinguishable from the original experimental data. Such simulated data can be used to validate assumptions, and make inferences on specified population targets that are accompanied by a measure of prediction reliability. We demonstrate use of the forecaster by employing N = 22 PK/PD parameter sets for an orally administered analgesic.

Bias↗
PubMed1999

[The trends of new drug development in the 21st century].

The trends of new drug development in the 21st century were described. First, the history of drug development including that of the drug delivery system (DDS) was shown. Then, the recent drugs and therapeutic technology were discussed in detail. These topics are biomedicine, gene related technology, vaccine, hybrid artificial organ, chemical and phage library, fetal growth hormone, cell therapy, humanized anti-body and Viagra. In addition, some natural products were introduced, emphasizing the relationship between food and human health. Finally, I stated my opinion about the new drug development in the 21st century in Japan.

Biopharmaceutics↗
PubMed1994

The new drug approvals of 1990, 1991, and 1992: trends in drug development.

Efforts to speed the development and review of new drugs have increased sharply in recent years. This report, which is the third in a series on trends in drug development, examines the new drug approvals of 1990, 1991, and 1992. During the 3-year study period, the Food and Drug Administration (FDA) approved 79 new drugs, 74 of which met the Center for the Study of Drug Development's definition of a new chemical entity (NCE). Of the 74 NCEs, 36 (49%) were considered by the FDA to represent notable therapeutic gains and were selected for "priority" review (i.e., drugs rated 1P, 1A, 1AA, and 1B), and 38 (51%) were considered to represent little or no gain and received "standard" reviews (i.e., drugs rated 1S and 1C). Investigational new drug application (IND) filing and new drug application (NDA) submission dates on all 74 drugs were obtained from responses to our manufacturer surveys as well as from FDA and public sources. The mean length of the clinical phase (IND filing to NDA submission) was 6.1 years and that of the review phase (NDA submission to approval) was 2.6 years. Of the 74 NCEs, 43 (58%) were available in foreign markets at least 1 year before U.S. approval, with a mean of 5.6 years of foreign marketing. In general, 1990 to 1992 figures are similar to those in the last half of the 1980s.

Drug Approval↗
PubMed1990

The role of ethnopharmacology in drug development.

There are 119 drugs of known structure that are still extracted from higher plants and used globally in allopathic medicine. About 74% of these were discovered by chemists who were attempting to identify the chemical substances in the plants that were responsible for their medical uses by humans. These 119 plant-derived drugs are produced commercially from less than 90 species of higher plants. Since there are at least 250,000 species of higher plants on earth, it is logical to presume that many more useful drugs will be found in the plant kingdom if the search for these entities is carried out in a logical and systematic manner. The first and most important stage in a drug development programme using plants as the starting material should be the collection and analysis of information on the use(s) of the plant(s) by various indigenous cultures. Ethnobotany, ethnomedicine, folk medicine and traditional medicine can provide information that is useful as a 'pre-screen' to select plants for experimental pharmacological studies. Examples are given to illustrate how data from ethnomedicine can be analysed with the aim of selecting a reasonable number of plants to be tested in bioassay systems that are believed to predict the action of these drugs in humans. The ultimate goal of ethnopharmacology should be to identify drugs to alleviate human illness via a thorough analysis of plants alleged to be useful in human cultures throughout the world. Problems and prospects involved in attaining this goal are discussed.

Drug Evaluation, Preclinical↗
PubMed2026

The Computational Revolution in Natural Product Research: A Data-Driven Roadmap for Next-Generation Drug Development.

Natural products (NPs) have historically provided the foundational scaffolds for drug development, yet traditional bioprospecting faces critical limitations: high rediscovery rates, laborious isolation workflows, and substantial attrition during clinical translation. The emergence of big data technologies is fundamentally transforming this landscape, enabling a shift from serendipity-based discovery toward systematic, data-driven approaches. This review examines how the integration of artificial intelligence (AI), machine learning (ML), and multi-omics datasets is accelerating natural product research across three key domains: (1) genome mining for biosynthetic gene cluster identification using platforms such as antiSMASH, (2) cheminformatics-driven prediction of structure-activity relationships and ADMET properties, and (3) metabolomics-guided dereplication to prioritize novel bioactive scaffolds. We evaluate the convergence of genomics, metabolomics, and computational chemistry in enabling in silico lead optimization and the discovery of cryptic metabolites from previously inaccessible microbial taxa. While challenges in data standardization and scalability persist, the synergy between big data and NP research is accelerating clinical translation. Despite persistent challenges in data standardization, scalability, and equitable benefit-sharing, the convergence of big data and NP research is poised to redefine drug development. These advances position computational NP research as a cornerstone of next-generation drug development.

big data analytics↗
PubMed1995

Rare diseases, drug development, and AIDS: the impact of the Orphan Drug Act.

The Orphan Drug Act provides public subsidies and incentives to spur the development of drugs for rare diseases--drugs that the private sector might otherwise consider unprofitable to produce. Although the act has achieved numerous successes, the high prices and extraordinary sales generated by some orphan drugs lead to a pivotal policy question: how can the act be used to meet the legislative goal of stimulating drug development for small patient populations without resulting in prices that make drugs inaccessible? This question is explored using the example of AIDS drugs, many of which received subsidies under the act, to illustrate central points. The history of the act, its weaknesses, and strategies for reform are described as well.

AIDS-Related Opportunistic Infections↗
PubMedDate not supplied

Chemopreventive drug development: perspectives and progress.

Chemoprevention drug development has the goal of identifying safe and effective chemopreventive agents for clinical use. Several distinctive strategies are pursued in developing chemopreventive agents: (a) identifying and validating predysplastic and early dysplastic lesions that can be used instead of cancers as endpoints for measuring chemopreventive activity; (b) identifying and testing candidate agents based on considerations of mechanisms of action; (c) evaluating combinations of agents with potential for maximizing efficacy and minimizing toxicity; and (d) applying a systematic methodology for identifying and ranking candidate agents at each stage of development to ensure discovery of the best agents and most effective use of available resources. This article discusses 22 drugs and three drug combinations which have reached an advanced stage of development as chemopreventive agents. The first generation of drugs are the most advanced, now being in Phase II and Phase III clinical trials. These drugs include several retinoids [vitamin A, 13-cis-retinoic acid, all-trans-N-(4-hydroxyphenyl)retinamide], calcium, beta-carotene, tamoxifen, and finasteride. The second generation drugs are those in Phase I clinical trials. From most to least advanced, these drugs are 2-difluoromethylornithine, sulindac, piroxicam, oltipraz, N-acetyl-I-cysteine, aspirin, ibuprofen, carbenoxolone, 18 beta-glycyrrhetinic acid, and the combination of 2-difluoromethylornithine with piroxicam. The third generation includes agents with significant evidence of chemopreventive activity in animal models. These agents are now in preclinical toxicity testing. They are S-allyl-I-cysteine, phenhexyl isothiocyanate, curcumin, ellagic acid, fumaric acid, fluasterone, and the combinations of all-trans-N-(4-hydroxyphenyl)retinamide with oltipraz and all-trans-N-(4-hydroxyphenyl) retinamide with tamoxifen.

Animals↗
PubMed1988

Detection of populations at risk and problem drugs during drug development and in pharmacotherapy.

Rational drug therapy requires knowledge about the ratio of risk (adverse drug reaction) to benefit (therapeutic efficacy) for all drugs to be used in humans. However, with newly marketed drugs, the risk/benefit ratio is usually not sufficiently known. Safety is often less well defined than efficacy. This is the result of the present mode of drug development. Premarketing studies are conducted in comparatively small, homogenous populations over relatively short time intervals and under standardized conditions. Only after marketing are larger, more diversified populations exposed over prolonged times, often under uncontrolled conditions. Adverse drug reactions (ADRs) are the result of either overdosage, or allergic or idiosyncratic reactions. They can be life-threatening or mild. Some of the ADRs are common (greater than 1:10); others are very rare (less than 1:1000). The overall rate of ADR occurrence in ambulatory and hospitalized patients is high enough to have significant socioeconomic consequences. Some of the risk populations can be suspected a priori: elderly, multimorbid patients and patients with compromised drug elimination who may be overdosed if the regimens are not appropriately modified. Some problem drugs may be recognized if they display one or more of the following characteristics: narrow therapeutic index, steep dose-effect relationship, nonlinear kinetics, variable bioavailability, and pharmacogenetically determined kinetics. Other individuals at risk, however, may not be readily identifiable. They develop allergic and idiosyncratic reactions after drug exposure without exhibiting easily recognizable predisposing factors. In order to determine the number of individuals so affected, and the associated drugs as quickly as possible during the developmental process, specific ADR surveillance measures are taken.(ABSTRACT TRUNCATED AT 250 WORDS)

Drug Hypersensitivity↗
PubMed1990

The place of simultaneous pharmacokinetic pharmacodynamic modeling in new drug development: trends and perspectives.

The potential applications in drug development of pharmacokinetic-pharmacodynamic modeling are numerous: optimal medication regimen, design of galenic forms, identification of specific effects of metabolites and enantiomers. Nevertheless, this methodology is presently under-used, as appears from an analysis of the literature. We examine this point as well as progress in both non-invasive pharmacodynamic measurement and specific experimental design that could lead to a future extension of PK-PD in toxicology and phase I drug development.

Drug Evaluation↗
PubMed1998

Exploratory studies: implications for drug development in Alzheimer's disease.

The process of drug development involves cycles of learning and confirming. In the learning phase of the cycle, data from studies are used to generate hypotheses; later studies are designed specifically to confirm these hypotheses. There is a growing realization that exploratory studies early in drug development are critical for the design of large confimatory clinical trials. For example, patients often differ from healthy volunteers in their tolerance of CNS compounds, so investigators should determine the maximum tolerated dose (MTD) in the patient population though a "bridging study" prior to designing Phase II efficacy trials. By performing well-controlled safety/tolerability studies with a small number of patients on an inpatient basis, researchers can avoid exposing large numbers of study participants to the wrong dose. Bridging studies also provide information on the approximate frequencies of various types of adverse events, which is very helpful in designing outpatient trials to confirm the safety profile. A second type of exploratory study, a "dynabridge study", is an early pharmacokinetic/pharmacodynamic (PK/PD) study in patients to measure drug concentrations and activities in the central compartment (assessed by sampling the CSF). Dynabridge studies can be used to optimize the dosing regimen, to confirm that the drug is affecting the targeted receptor, and to measure correlations between drug activity and proposed surrogate markers.

Alzheimer Disease↗
PubMed1998

Stable isotope techniques in early drug development: an economic evaluation.

Stable isotope labeled (SIL) drug methods are compared with standard methods for performing early (phases I and IIa) drug development studies (mass balance, bioavailability, single-dose volunteer and patient, multiple-dose volunteer and patient). SIL methods offer considerable reduction in the cost (> 50%) and number of subjects (67%) required for bioavailability and multiple-dose patient studies. Moreover, a complete early drug development program is described for optimally combining SIL and standard studies, which can reduce cost by 23% and number of subjects by 36% compared with a program using standard methods. These reductions should result in development time savings of at least one year.

Clinical Trials, Phase I as Topic↗
PubMed1998

Drug interactions at the renal level. Implications for drug development.

The kidney plays a major role in the elimination of drugs. The purpose of this paper is to: (i) review the mechanisms of renal elimination; (ii) identify potential mechanisms for renal drug interactions; (iii) review in vitro and in vivo animal models for studying renal elimination mechanisms and identifying potential drug-drug interactions; (iv) review experimental designs used in identifying drug-drug interactions in humans with an emphasis on gaining information regarding the mechanism of the interaction; and (v) make recommendations regarding the potential for renal drug interactions in drug development. It is concluded that clinically significant drug interactions resulting in toxicity because of some mechanism at the renal level appear to be relatively rare and that in vitro screening should not be done on all drugs during drug development. Five potential mechanisms exist for drug interactions at the renal level: (i) a displacement of bound drug resulting in an increase in drug excretion via an increase in glomerular filtration; (ii) competition at a tubular secretion site resulting in a decrease in drug excretion; (iii) competition at the tubular reabsorption site resulting in an increase in drug excretion; (iv) a change in urinary pH and/or flow that may increase or decrease drug excretion depending on the pKa of the drug; and (v) inhibition of renal drug metabolism. The most well known renal drug interaction is competitive inhibition of tubular secretion, ultimately leading to an increase in plasma drug concentration. Only when renal clearance is a major contributor to the total clearance (> 30%) and plasma concentrations are greater than the Michaelis-Menten transport constant does the potential exist for clinically significant renal drug-drug interactions because only then does nonlinear pharmacokinetics become evident. The potential for drug interactions is small when renal clearance is less than 20 to 30% of the total clearance and/or when plasma concentrations are less than the Michaelis-Menten transport constant, unless the drug has a narrow therapeutic window.

Animals↗
PubMed1998

[Development of anti-cancer drugs under new renewed GCP--from the viewpoint of drug development company developer].

During the past 7 years since the enforcement of Japan's first GCP in October 1990, various standards and guidelines have been introduced in Japan. On the other hand, the harmonization of GCP has been the subject of major discussion at ICH in order to allow the mutual acceptance of clinical data from different countries. In order to further improve the reliability and consistency of clinical data and the ethics of clinical trials in Japan, the new GCP was enforced in April 1997. A clinical study is conducted by the sponsor, but will only be successful with the collaboration of trial subjects, medical institutions, heads of medical institutions, investigators, subinvestigators, pharmacists, nurses, laboratory technicians, and other assisting staff. Before the full enforcement of the new GCP, we, as sponsors of clinical trials, carried out a survey of the current status of clinical trials centering on the reactions of medical institutions to the new GCP, future of clinical trials on anti-cancer drugs in Japan, and differences in time from clinical trials to registration in Japan, the United State and Europe. We sent a questionnaire by facsimile to 21 pharmaceutical companies which have developed or are developing anti-cancer drugs and obtained replies from 20 companies (95%) from August 25 to 30, 1997. This paper reports issues concerning clinical trials on anti-cancer drugs based on the results of our survey.

Antineoplastic Agents↗
PubMed1992

The decline in new drug development.

The future depends on innovation, not imitation. New drug development can be encouraged in a number of ways (Table 4), and the rewards are great. Who knows what dramatic drug discoveries remain to be found in a new synthetic compound, a fresh soil sample, or a plant obtained from some pristine forest? In any event, let us all hope that the molecular roulette that has governed drug development in the past will be replaced by a more rational, and less empirical, approach.

Chemistry, Pharmaceutical↗