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1. Study?Design?for?Multiple?Batch?Analyses??

1. ¶àÅú´Î·ÖÎöµÄÑо¿Éè¼Æ?

Analyses of batch effects on clinical endpoints (i.e., batch effect analyses) should be considered when drug product batches exhibit variations (e.g., a variation in chemical composition), potentially affecting clinical outcomes. These are additional analyses beyond the standard primary efficacy analyses usually performed. Standard analyses involve comparing a control group to a treatment group composed of subjects pooled across different batches. The batches that are chosen should be representative of the marketing batches and should not be too homogenous. The goal of these analyses is to quantify potential heterogeneity in clinical outcomes for subjects who receive different batches in the study. This is in principle similar to other types of subgroup analyses. 32

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If batch effect analyses are warranted, the sponsor should design clinical studies to facilitate these analyses, pre-specify in the protocols how these analyses will be carried out, discuss with the appropriate OND review division the pre-planned models for these analyses, and present the results of these analyses in the clinical study report. Batch effect analyses are usually exploratory, with no formal requirement of control of the Type I error rate. The remainder of this section provides more details on our recommendations for clinical study design, as well as modeling and presentation of clinical study results, to accommodate batch effect analyses.

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Randomization of subjects to different batches in each site is highly recommended to facilitate batch effect analyses. For instance, a study of three different batches is conceptually similar to a study with three different randomized dosage groups and one control group. If subjects are not randomized to different batches, a direct comparison of clinical outcomes in different batches can be confounded by other effects. For example, if drug products supplied to any given site are only from one batch rather than from multiple batches, then a direct comparison of clinical outcomes in different batches is confounded with site effects on clinical outcomes.

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32 See Section 5.7 of ICH E9 Statistical Principles for Clinical Trials. 32²Î¼û¡¶ICH E9

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The sponsor should also ensure that subjects randomized to a certain batch group receive study drug from the same batch for the duration of the study. In situations where this may not be possible, the batch effect analyses may only be able to estimate a batch sequence effect.

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With regard to modeling and presentation of results from batch effect analyses, the sponsor should include summary tables and/or forest plots displaying estimates and confidence intervals of clinical outcomes or treatment effect by batch, describe the pre-planned models used to generate these results, assess possible heterogeneity of clinical outcomes in subjects that receive different batches, and describe the statistical measures of heterogeneity and statistical tests of homogeneity used. In addition, the sponsor should provide a summary of the subjects¡¯ baseline characteristics by batch to explore possible imbalances in the subjects¡¯ baseline characteristics between batches and identify possible confounders of batch effect on clinical outcomes.

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2.?Dose©\Response?Effect??

2.¼ÁÁ¿©\ÏìӦЧӦ?

Another approach to show that clinical response to a botanical drug will not be affected by variations of different batches is to demonstrate that the drug¡¯s effect on clinical outcomes is not sensitive to dose, while also demonstrating that the studied doses are more effective than placebo or control, or not inferior to active treatment. If a randomized, multiple-dose, parallel group design, Phase 3 study demonstrates a similar treatment effect across multiple doses, concerns about the impact of variability in chemical composition across batches may be diminished. Therefore, to facilitate the Agency¡¯s evaluation of the effects of doses on clinical outcomes, the sponsor should summarize the results of different doses on clinical outcomes, including estimates and confidence intervals of treatment effects by dose displayed in tables and/or forest plots, in the clinical study report.

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3.Clinical?Studies?of?Botanical?Drugs?for?Serious?Conditions?

3.ÓÃÓÚÑÏÖØ¼²²¡µÄÖ²ÎïÒ©Æ·µÄÁÙ´²Ñо¿?

While extensive anecdotal human experience for some botanical drugs may exist, not knowing the active constituent(s) and/or mechanisms of action may cast doubt on the drug¡¯s presumed efficacy. Lack of scientifically reliable and relevant data to support efficacy may raise ethical concerns for clinical studies evaluating the botanical drug alone, especially for serious conditions. In these cases, an ¡°add-on to standard care versus standard care¡± design is preferred to a ¡°stand-alone versus control¡± design in clinical studies for serious conditions. However, add-on designs present the possibility of an adverse interaction between the standard of care and the botanical drug. If such an interaction is possible and strong evidence is available to support the presumed efficacy of the botanical drug alone, alternative designs (e.g., adding a third arm of botanical drug alone) should be considered.

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4.?Other?Study?Design?Issues??

4.?ÆäËüÑо¿Éè¼ÆÎÊÌâ?

When the rationale for developing certain botanical drug products is based on prior clinical experience in alternative medical systems (e.g., Ayurveda, traditional Chinese medicine, Unani, Sidha, and other herbal medicine and pharmacognosy textbooks), the sponsor may propose to incorporate traditional practices into their clinical protocols. For example, patients may be selected or grouped based on alternative medical theory or practice and treated with specific botanical regimens accordingly, or the final dosage form may be prepared by individual patients according to traditional Chinese or Indian methods.

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These unconventional measures should be considered individually and could be acceptable if they will

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help ensure or enhance the therapeutic effect for an acceptable indication and can be described and translated into practical instructions for use in the labeling for patients and healthcare providers in the United States. The sponsor contemplating such approaches should consult with the appropriate OND review division.

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G.?Applicability?of?Combination?Drug?Regulations??G.¸´·½Ò©Æ··¨¹æµÄÊÊÓÃÐÔ?

For a fixed-combination drug product, current regulations require sponsors to demonstrate each component¡¯s contribution toward overall efficacy and/or safety. 33However, these regulations generally do not apply to naturally derived mixtures, such as those found within a single botanical raw material. Botanical drug products derived from a single botanical raw material are generally not considered fixed-combination drugs because the entire botanical mixture generally is considered to be the active ingredient.

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Botanical drug products derived from multiple botanical raw materials are currently considered fixed-combination drugs. However, the Agency recognizes that demonstrating each botanical raw material¡¯s contribution to efficacy and safety in a product with multiple botanical raw materials may not always be feasible. The Agency is currently reviewing the requirements for fixed-combination drugs and how they should be applied to botanical drug products.

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Until the Agency issues further guidance or policy specific to the application of these regulations to fixed-combination botanical drug products, nonclinical data from animal disease models or

pharmacological in vitro assays may be useful to show the contribution of individual components34 to the claimed effects.

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33 See ¡ì300.50 and 330.10(a)(4)(iv). 33

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34 In this context, a component refers to a mixture derived from a specific botanical raw material. 34 ÔÚÕâÖÖÇé¿öÏ£¬Ò»¸ö³É·ÖÖ¸Ô´ÓÚÒ»ÖÖÌØ¶¨µÄÖ²ÎïÔ­Ò©²ÄµÄÒ»ÖÖ»ìºÏÎï¡£

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