Medical network May 19 - to solve the problem of pediatric population need medication, to further encourage the development of pediatric drugs, maximum use of existing data, reduce unnecessary pediatric research, through the data extrapolation to improve and enrich the instruction in the pediatric population drug information, to guide the clinical medication, the administration of the state food and drug supervision and administration to make the "adult medicine data extrapolation to the pediatric population technical guiding principles (see annex), are hereby issued. 

 

I inform you that. 

 

Attachment: the technical guiding principles of adult drug data extrapolated to the pediatric population 

 

The general administration of food and drug administration 

 

On May 16, 2017 

 

Technical guidelines for the use of adult drug data to be extrapolated to the pediatric population 

 

1 overview 

 

Currently, there is widespread use of drug overstatement in the global paediatric population, and China is no exception. The main reason is included in pediatric patients (hereinafter referred to as "children") to conduct clinical trials of special ethical challenges (such as the use of placebo), practical difficulties (e.g., curative effect evaluation, need to provide special protection for children in the study), growth/development significant differences, etc., makes the difficulty of the pediatric population in drug clinical trials is much greater than adults. Based on the above reasons, difficult to confirmed by large-scale clinical trials for children with research data, support for the safety and efficacy of each specific age groups. From the ethical considerations, adopting new techniques and establishing new methods to reduce the clinical trials of unnecessary paediatric patients, and to minimize the pain of the pediatric population. Maximum use of existing data, therefore, as far as possible, reduce the number of pediatric population drug clinical trial subjects, through data extrapolation to improve drug pediatric population and rich information, to guide the clinical medication, is to improve the guarantee drug is safe and effective in children with one of the most effective way. 

 

Typically, data extrapolation is mainly aimed at the validity data to obtain a clear dose. However, in some cases, it is important to consider the safety of the drug at different age groups, especially the long-term safety associated with growth and development. 

 

This guideline applies only to existing products of China's adult data extrapolation to the pediatric population in China, no Chinese adult data extrapolation is not reflected in this guiding principle. Considering the target group, the differences between the treatment and drug properties, data extrapolation method has its diversity and flexibility, this guiding principle is only put forward the general requirements of data extrapolation. Encourage research and development to communicate with regulators in the early stages of development of drug use in the pediatric community. 

 

This guideline is only on behalf of the drug regulatory agency of the current views and understanding, provide the reference for the research and development enterprise, do not have mandatory binding, with the progress of the scientific research, relevant content in this guideline will continue to improve. 

 

Application of this guideline, should the reference drug at the same time quality control standard for clinical trials (GCP), people with technical requirements for drug registration international coordination meeting (ICH) and other related technical guidelines published at home and abroad, such as the technical guidelines of pediatric population drug clinical trials in the pediatric population pharmacokinetic study technical guiding principles, etc. 

 

2 the concept 

 

Extrapolation method has been widely used in drug development, such as in vitro experiment or extrapolated to human trials, animal test data to determine the first doses and predicting the effective dose; The health volunteers' pharmacodynamic data was extrapolated to the patient population; Extrapolation of the pharmacodynamic data between drugs of the same mechanism or similar mechanisms. 

 

Data extrapolation, often referred to as: the scientific research methods, research information will be known to people and conclusion, extended to the unknown people (target groups) to reduce unnecessary study in unknown the crowd. 

 

Data extrapolation in this guiding principle is to point to: through the scientific research method, the known information, research on the adults and the conclusion, extension to unknown pediatric populations (target groups) to reduce unnecessary study in unknown pediatric population. 

 

Three processes 

 

Extrapolation of data includes the establishment of extrapolation, design extrapolation, extrapolation of extrapolation, and the formulation of major factors such as reducing uncertainty and risk strategy. Extrapolation hypothesis, extrapolation scheme and the analysis of extrapolation is a sequential and cycling process, this process runs through the whole life cycle of pediatric population drug development, including the listed before and after listing. 

 

Create extrapolation assumptions 

 

Integration of the known data, evaluation of target population and people known the similarities and differences, with the aid of modeling simulation, specifically extrapolation hypothesis, prediction index. 

 

The known data sources include in vitro test, animal experiments and epidemiological studies, diagnostic studies, pharmacokinetic (PK) and pharmacodynamics (PD) study, clinical trials and clinical observational studies, similar to drug research, literature, etc. 

 

"Similarity" similarity assessment including disease (etiology, pathology, physiology, clinical manifestation, course features, etc.), drug metabolism in human body and function similarity (pharmacokinetics, pharmacodynamics, pharmacological mechanism, etc.), drug exposure and effect relationship between drug and clinical effectiveness and safety of similarity evaluation index and standard consistency, etc. 

 

In general, the higher the likelihood of predicting a similar degree of similarity between people, the greater the probability of extrapolation, the lower the need for additional research data. On the contrary, if the lower the degree of similarity between predicted population or is hard to predict, or, the more the influence factors of prediction accuracy or influence factors is difficult to clear, the smaller the possibility of extrapolation, the greater the need for extra research data. 

 

According to the known data the extrapolation hypothesis in the known population and target groups of similar degree, extrapolation model is divided into the following three: completely extrapolation, part of the extrapolation and without extrapolation. 

 

The "totally extrapolated" model is that the target population is highly similar to the known population, and the hypothesis is highly accurate. 

 

The "partial extrapolation" pattern is that there is a certain similarity between the target population and the known population, and/or hypothesis (prediction) uncertainty. 

 

The "no extrapolation" pattern is that there is no similarity between the target population and the known population, and/or hypothesis (prediction) is highly inaccurate. 

 

Design extrapolation plan 

 

Based on the assumption extrapolation, target population study plan, including what data can be directly obtained through extrapolation, which need to simplify design of clinical trials or clinical trials for complete system. 

 

Carry out extrapolation analysis 

 

Explain the limited data obtained in the target population, verify extrapolation hypothesis, confirm/verify that the population is similar to the target group. If the hypothesis is not verified, the modeling simulation is improved, the extrapolation and extrapolation are adjusted and the extrapolation is analyzed. When necessary, collect data or consider the use of data segments. 

 

3.4 reduces uncertainty and risk strategy 

 

The reliability of data extrapolation should be fully evaluated, the uncertainty and risk are clearly defined, and the strategy of reducing uncertainty and risk is proposed. It may be difficult to explain these uncertainties and risks before going public, if they have limited validation data based on the target population, and they need to develop a post-ipo research plan. 

 

Modeling simulation 

 

Modeling Simulation (Modeling and Simulation, M&S) is based on the data (in vitro, animal, clinical, literature), assuming (based on mathematical/statistical models to describe the data), learning (reserve hypothesis related information), prediction (based on the hypothesis of data Simulation prediction and optimization design of experiment) and confirmed (compared with external data) method of the data model. 

 

Modeling simulation is a method of data analysis is used to collect data, describe the same crowd signs and quantitative assessment of differences between groups, prediction method for the decision of follow-up studies, and pediatric population cannot entirely replace drug clinical trials. The sample size of the sample was determined by the modeling simulation, and the dosage of the drug was predicted. Modeling simulation is complex and requires consideration of various factors related to target indications, target populations, and experimental drugs. 

 

It is important to note that in view of the deficiency of the existing knowledge theory, for human growth and development at different stages of differences can't accurate judgment, can bring difficulties to modeling simulation. Extrapolating the extrapolation from the outside world requires sufficient consideration for the impact of knowledge limitations and uncertainties on modeling the results of modeling data. 

 

Basic principles and requirements 

 

Push the product data on adults to the pediatric population, products need to be on the data of Chinese adults at the same time, according to whether the foreign pediatric population has approved indications, whether for pediatric population in the domestic and overseas references (or other supporting data), divided into the following three conditions to carry out the extrapolation. 

 

Data on Chinese adult data and the indications for pediatric population have been approved abroad 

 

In the pediatric population data, overseas Chinese adult indications have been approved, the first evaluation of different countries or areas disease epidemiology, etiology, pathogenesis and prognosis of disease progression and so on whether there is a difference; On this basis, the evaluation of adult patients with test data at home and abroad, the key evaluation racial differences, including the existence of clinical pharmacology, pharmacokinetic and pharmacodynamic and therapeutics (medical practice effectiveness, safety data), and other differences, such as in many other aspects of the difference has sufficient evidence to show that there is no significant difference in comparison, pediatric population can continue to use the foreign drug clinical trial data. 

 

The data are available for use in Chinese adult data and in the reference literature of children at home and abroad 

 

In principle, prospective research is an important basis for the formulation and improvement of the specification. But in terms of children, some drugs have been widely used in clinical practice. Indications for pediatric population data of China's adult has not been approved, but have a pediatric population evidence of clinical application at home and abroad, can through the system evaluation method, the existing research evidence as revision, perfect the specification in the pediatric population the main basis of medical information. 

 

The system evaluation is divided into two categories: quantitative and qualitative. If there is heterogeneity between the studies that are included, it cannot be quantified, and it can be done in a qualitative way. Two types of system evaluation in evaluation process and data quality has strict requirements, steps include: determine the topic, making system evaluation research program, retrieve the documents, screening of literature, evaluate the quality of literature, extract the data, analysis and reporting results, explained the results, writing research report. 

 

5.3 is the only extrapolation of Chinese adult data 

 

In China only adult data, there is no indication or research data to pediatric population situation at home and abroad, the adult of rational use of clinical trial data can avoid unnecessary pediatric group to conduct clinical trials. Based on existing knowledge, adult clinical trial data is limited to the effect data of the pediatric population. And the availability of safety data for the paediatric population usually involves testing in the pediatric population. 

 

There is a scientific basis for decision-making (or extrapolation) of whether the clinical trials of adult clinical trials are extrapolated and extrapolated. First, you need to all available information and data to carry on the comprehensive analysis, including the differences between the different ages people organ function and influence on pharmacological characteristics, disease knowledge, epidemiological situation, drug non-clinical experimental data, the same or similar mechanism between adult and pediatric populations of PK and PD, the difference of clinical effectiveness and safety, etc. Then, make a decision (or inference) from the following two aspects: 

 

(1) whether the disease process and therapeutic response of target indications are similar among adults and pediatric populations; 

 

(2) the Exposure effect of the drug (Exposure to Response relationship) is similar between adults and pediatric populations. 

 

If the comprehensive analysis of the information and data they support (1) and (2) are similar, so, can choose the appropriate tests pediatric populations, through drug exposure (PK) in the body of the bridge, the adult dose extrapolation for pediatric population dose. Then, if necessary, use the proposed dosage in certain pediatric populations in randomized controlled trials, the key is to get the crowd safety data, at the same time, the rationality of the validation to dose. 

 

There is a special case, if (1) and (2) are similar, but only by local exposure to play a role of efficacy and there is sufficient evidence to support the proposed for pediatric population dose with adult dose (such as local external use drugs) at the same time, can no longer carry out pediatric population PK test to explore the dose, just draw the dose of tests in certain pediatric populations, the key is to get the crowd safety data, at the same time, the rationality of the validation to dose. 

 

If the comprehensive analysis of the information and data they support (1), (2) similar or not is difficult to determine, then can choose appropriate PK/PD experiment in the pediatric population to reveal the relationship between the drug in the pediatric population exposure effect in vivo, and comparing with adult body exposed effect relationship. If can prove extrapolation, dosage, the use of the proposed tests in certain pediatric populations, the key is to get the crowd safety data, at the same time, the rationality of the validation to dose. If the comparison results suggest that there are no conditions for extrapolating the clinical data of adults, then clinical trials of the paediatric patients with a comprehensive system need to be carried out. 

 

If the comprehensive analysis of the information and data they support (1) and (2) are not similar or is difficult to determine, and don't have the requirement of adult efficacy data extrapolation, so need to carry out a comprehensive system of pediatric population drug clinical trials. 

 

The FDA's paediatric population study design and extrapolation decision flowchart (see figure 1) for reference. 

 

 

Figure 1 studies design and extrapolation of extrapolation decisions