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Understanding the Importance of Repeat Analysis in Study Samples

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Quantitative analysis of study samples is a crucial component of the therapeutic development process. Techniques such as Enzyme-Linked Immunosorbent Assay (ELISA), Quantitative Polymerase Chain Reaction (q-PCR), and Liquid Chromatography Mass Spectrometry (LC/MS) are examples of laboratory techniques routinely used to analyze samples to quantitate therapeutics of interest in clinical and nonclinical studies. Oftentimes this includes the use of plates containing wells within which samples from subject participants are transferred for quantitative analysis. The results of these readings are then presented in a laboratory report that generally supports formal submissions to regulators for approval of a treatment.

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Key Techniques in Quantitative Analysis: Assignable Causes and Acceptance Criteria

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A typical quantitative laboratory report will include a table that lists each of the plates and whether their results were accepted or rejected. Quality control samples are generally included on each plate (although not exclusively as other non-subject samples may also be included). This is done to inform the scientist if the method is working properly and if the results from the study samples on that plate are reliable. If the plate controls do not meet a predefined set of acceptance criteria, then the plate is considered unacceptable, and the results are not used.

It is important that the reporting of these results is clear, descriptive, and transparent not only in cases where entire plates are deemed unacceptable, but especially when decisions are made to repeat the analysis of specific, individual samples due to an assignable cause from an otherwise acceptable plate. Some examples of an assignable cause might be the original result was outside the method quantitative range, there was a documented sample preparation error, or there was an equipment malfunction.

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Comprehensive Laboratory Report

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Repeating the analysis of individual study samples due to an assignable cause is a common component of these types of analyses. The vast majority of reasons for repeating the samples are easily explainable. To satisfy the goal of making these results clear, descriptive, and transparent, a common best practice is to present in the report a table that lists the individual study samples that underwent repeat analyses. The table includes the specific study sample and any other identifying information (e.g., Group No., tissue type, biological matrix, etc.), along with the original result, original plate number, reason for repeating, repeated result, repeated plate number, the final reported result, and the rationale for selecting the final result. This collection of information is closely aligned with suggestions found in regulatory guidance documents (See for example, the US FDA Guidance document on Method Validation, 2018; https://www.fda.gov/regulatory-information/search-fda-guidance-documents/bioanalytical-method-validation-guidance-industry).

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The Repeat Analysis Table

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Study samples that were repeated due to being a part of an unacceptable plate are generally not needed in the Repeat Analysis table as none of their results would be considered reliable. The Repeat Analysis table provides a clear and transparent list of all samples that were repeated from otherwise acceptable plates, along with various descriptions and rationales for each study sample. Here is a generic example of a Repeat Analysis table that is used for one of our clients:

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Each laboratory report also contains a main table listing the final quantitative results for all subject samples analyzed in the study. The final results in the main table for each of the study samples that were repeated should match the results for these same samples listed in the “Final Reported Result” column of the Repeat Analysis table.

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Differentiating Repeat Analysis and Incurred Sample Reanalysis (ISR)

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It should be noted that the above discussion regarding repeat analyses should not be confused with another type of reanalysis that is a normal component of the therapeutic discovery process referred to as Incurred Sample Reanalysis (ISR). ISR refers to the requirement that study samples be repeated as an assessment of the reliability of the final reported results as demonstrated by the method. The original and repeated results are listed out in their own table and a difference between the two is expressed as a percentage.

The repeated ISR result for each sample is not reported in the overall main study sample table. ISR differs in that it is an assessment of the reliability of a sampling of results and the method, whereas the repeat analysis in the discussion above is done to attain an acceptable result for a particular individual sample.

[/fusion_text][fusion_imageframe image_id=”19477|full” aspect_ratio=”” custom_aspect_ratio=”100″ aspect_ratio_position=”” skip_lazy_load=”” lightbox=”no” gallery_id=”” lightbox_image=”” lightbox_image_id=”” alt=”” link=”” linktarget=”_self” hide_on_mobile=”small-visibility,medium-visibility,large-visibility” sticky_display=”normal,sticky” class=”” id=”” max_width=”” sticky_max_width=”” align_medium=”none” align_small=”none” align=”none” mask=”” custom_mask=”” mask_size=”” mask_custom_size=”” mask_position=”” mask_custom_position=”” mask_repeat=”” style_type=”” blur=”” stylecolor=”” hue=”” saturation=”” lightness=”” alpha=”” hover_type=”none” magnify_full_img=”” magnify_duration=”120″ scroll_height=”100″ scroll_speed=”1″ margin_top_medium=”” margin_right_medium=”” margin_bottom_medium=”” margin_left_medium=”” margin_top_small=”” margin_right_small=”” margin_bottom_small=”” margin_left_small=”” margin_top=”” margin_right=”” margin_bottom=”” margin_left=”” bordersize=”” bordercolor=”” borderradius=”” z_index=”” caption_style=”off” caption_align_medium=”none” caption_align_small=”none” caption_align=”none” caption_title=”” caption_text=”” caption_title_tag=”2″ fusion_font_family_caption_title_font=”” fusion_font_variant_caption_title_font=”” caption_title_size=”” caption_title_line_height=”” caption_title_letter_spacing=”” caption_title_transform=”” caption_title_color=”” caption_background_color=”” fusion_font_family_caption_text_font=”” fusion_font_variant_caption_text_font=”” caption_text_size=”” caption_text_line_height=”” caption_text_letter_spacing=”” caption_text_transform=”” caption_text_color=”” caption_border_color=”” caption_overlay_color=”” caption_margin_top=”” caption_margin_right=”” caption_margin_bottom=”” caption_margin_left=”” animation_type=”” animation_direction=”left” animation_color=”” animation_speed=”0.3″ animation_delay=”0″ animation_offset=”” filter_hue=”0″ filter_saturation=”100″ filter_brightness=”100″ filter_contrast=”100″ filter_invert=”0″ filter_sepia=”0″ filter_opacity=”100″ filter_blur=”0″ filter_hue_hover=”0″ filter_saturation_hover=”100″ filter_brightness_hover=”100″ filter_contrast_hover=”100″ filter_invert_hover=”0″ filter_sepia_hover=”0″ filter_opacity_hover=”100″ filter_blur_hover=”0″]https://www.celegence.com/wp-content/uploads/2024/05/Reporting-Repeat-Analysis-of-an-Individual-Study-Sample-Due-to-an-Assignable-Cause-inblog.png[/fusion_imageframe][fusion_separator style_type=”none” hide_on_mobile=”small-visibility,medium-visibility,large-visibility” class=”” id=”” sep_color=”” top_margin=”30px” bottom_margin=”” border_size=”” icon=”” icon_circle=”” icon_circle_color=”” width=”” alignment=”center” /][fusion_title title_type=”text” marquee_direction=”left” marquee_speed=”15000″ rotation_effect=”bounceIn” display_time=”1200″ highlight_effect=”circle” loop_animation=”off” highlight_width=”9″ highlight_top_margin=”0″ before_text=”” rotation_text=”” highlight_text=”” after_text=”” title_link=”off” link_url=”” link_target=”_self” hide_on_mobile=”small-visibility,medium-visibility,large-visibility” sticky_display=”normal,sticky” class=”” id=”” content_align_medium=”” content_align_small=”” content_align=”left” size=”2″ animated_font_size=”” fusion_font_family_title_font=”” fusion_font_variant_title_font=”” font_size=”” line_height=”” letter_spacing=”” text_transform=”” text_color=”” hue=”” saturation=”” lightness=”” alpha=”” animated_text_color=”” text_shadow=”no” text_shadow_vertical=”” text_shadow_horizontal=”” text_shadow_blur=”0″ text_shadow_color=”” text_stroke=”no” text_stroke_size=”1″ text_stroke_color=”” text_overflow=”none” margin_top_medium=”” margin_right_medium=”” margin_bottom_medium=”” margin_left_medium=”” margin_top_small=”” margin_right_small=”” margin_bottom_small=”” margin_left_small=”” margin_top=”” margin_right=”” margin_bottom=”” margin_left=”” margin_top_mobile=”” margin_bottom_mobile=”” gradient_font=”no” gradient_start_color=”” gradient_end_color=”” gradient_start_position=”0″ gradient_end_position=”100″ gradient_type=”linear” radial_direction=”center center” linear_angle=”180″ highlight_color=”” style_type=”default” sep_color=”” link_color=”” link_hover_color=”” animation_type=”” animation_direction=”left” animation_color=”” animation_speed=”0.3″ animation_delay=”0″ animation_offset=””]

Ensuring Data Reliability

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Overall, repeating the analysis of study samples based on assignable causes is a common occurrence in regulated quantitative analysis. Creating a specific table that lists each of these samples, as well as the various rationales and other descriptive elements repeats, is a best practice that can go a long way in satisfying curiosities that arise during the regulated review and auditing process. Including these components in a clear and descriptive manner in a separate table of the laboratory report increases the likelihood of reviewers and auditors will be confident that the original results are reliable, the repeats were necessary, and the final reported concentrations in the overall study sample data table are reliable.

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Celegence’s Expertise: Your Partner for Expert Bioanalytical Services

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Led by CEO Sonia Veluchamy, at Celegence, we boast a diverse network of full-time writers and consultants, hailing from various scientific disciplines, with a particular specialization in the regulated bioanalytical domain. This extensive network empowers us to offer comprehensive services tailored to client programs necessitating adeptness in various writing methodologies pertinent to regulated bioanalysis. Among the pivotal subjects we address, the utilization and meticulous reporting of QC samples stand as a cornerstone.

We can be reached at info@celegence.com or contact us online for more information.

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About the Author

[/fusion_title][fusion_text columns=”” column_min_width=”” column_spacing=”” rule_style=”” rule_size=”” rule_color=”” hue=”” saturation=”” lightness=”” alpha=”” content_alignment_medium=”” content_alignment_small=”” content_alignment=”” hide_on_mobile=”small-visibility,medium-visibility,large-visibility” sticky_display=”normal,sticky” class=”” id=”” margin_top=”” margin_right=”” margin_bottom=”” margin_left=”” fusion_font_family_text_font=”” fusion_font_variant_text_font=”” font_size=”” line_height=”” letter_spacing=”” text_transform=”” text_color=”” animation_type=”” animation_direction=”left” animation_color=”” animation_speed=”0.3″ animation_delay=”0″ animation_offset=”” logics=””]This blog post is written by Jean-François Cazorla, our Scientific Writing Consultant, who has extensive experience and expertise in the field of regulated bioanalytical report writing. Jean’s 20+ years in the field includes overseeing the regulated QC and writing divisions in bioanalytical CRO environments, as well as the individual production of regulated bioanalytical documents for 250+ biopharmaceutical sponsors. During this time, he was involved in small and large molecule bioanalytical programs, with particular emphasis on producing immunogenicity and pharmacokinetic validation and sample analysis reports. He is currently a consultant for Celegence helping a major documentation contract with a Sponsor developing gene therapies.[/fusion_text][/fusion_builder_column][/fusion_builder_row][/fusion_builder_container]