CDP (Comparative Dissolution Profiles)

In Pharmaceutical Industries the Comparative Dissolution Profiles (CDP) is very important study.

For CDP study enovator sample is required along with our sample. 

The comparison factors can be expressed by two approaches: f1 (the difference factor) and f2 (the similarity factor). Two dissolution profiles to be considered similar and bioequivalent, f1 should be between 0 and 15 whereas f2 should be between 50 and 100.

Dissolution profiles data should be generated in a comparative manner as follows:

• At least 12 dosage units (e.g. tablets, capsules) of each batch must be tested individually, and mean and individual results reported. 
  
• The percentage of nominal content released are measured at a minimum of three (3) suitably spaced time points (excluding zero time point) to provide a profile for each batch (e.g. at 5, 15, 30 and 45 minutes, or as appropriate to achieve virtually complete dissolution).
• The batches are tested using the same apparatus and, if possible, on the same day.
• The stirrer used is normally a paddle at 50 rpm for tablets and a basket at 100 rpm for capsules. However, other systems or speeds may be used if adequately justified and validated.
• Test conditions are those used in routine quality control or, if dissolution is not part of routine quality control, any reasonable, validated method.
• The f2 value must be between 50 and 100.
• If more than 85 per cent of the active substance is dissolved within 15 minutes or before 15 minutes  in all tested batches, dissolution profiles are considered to be similar without the need to calculate the similarity factor.

In recent years, FDA has placed more emphasis on a dissolution profile comparison in the area of post-approval changes and biowaivers. Under appropriate test conditions, a dissolution profile can characterize the product more precisely than a single point dissolution test. A dissolution profile comparison between pre-change and post-change products for SUPAC related changes, or with different strengths, helps assure similarity in product performance and signals bioinequivalence.


Among several methods investigated for dissolution profile comparison, f2 is the simplest. Moore and Flanner proposed a model independent mathematical approach to compare the dissolution profile using two factors, f1 and f2 (1).



where Rt and Tt are the cumulative percentage dissolved at each of the selected n time points of the reference and test product respectively. The factor f1 is proportional to the average difference between the two profiles, where as factor f2 is inversely proportional to the average squared difference between the two profiles, with emphasis on the larger difference among all the time-points. The factor f2 measures the closeness between the two profiles. Because of the nature of measurement, f1 was described as difference factor, and f2 as similarity factor (2). In dissolution profile comparisons, especially to assure similarity in product performance, regulatory interest is in knowing how similar the two curves are, and to have a measure which is more sensitive to large differences at any particular time point. For this reason, the f2 comparison has been the focus in Agency guidances.

Significant Changes in Stability sample analysis

As per ICH “significant change” the changes occur in the drug product during the stability study in Accelerated condition (ACC). 

 In general, “significant change” for a drug product is defined as:

1. A 5% change in assay from its initial value; or failure to meet the acceptance criteria for potency when using biological or immunological procedures; 

2. Any degradation product’s exceeding its acceptance criterion; 

3. Failure to meet the acceptance criteria for dissolution for 12 dosage units. 

4. Failure to meet the acceptance criterion for pH; 

5. Failure to meet the acceptance criteria for appearance, physical attributes, and functionality test (e.g., color, phase separation, re-suspendibility, caking, hardness, dose delivery per actuation); however, some changes in physical attributes (e.g., softening of suppositories, melting of creams) may be expected under accelerated conditions;     

An ANDA applicant should submit 6 months of accelerated stability  data and 6 months of long-term stability data at the time of submission.However, if 6 months of accelerated data show a significant change or failure of any attribute, the applicant should also submit 6 months of intermediate data at the time of submission.

If accelerated data show a significant change or failure of any attribute in one  or more batches, an applicant should submit intermediate data for all three batches. In addition, the submission should contain a failure analysis.

Case Study:

For Assay: As per above guidance if 5% change in assay from initial then it is significant change,

 e.g. if initial assay is 96.2% and 03 months ACC (40°C/75% RH) assay is 101.3% (different in assay from initial assay is 5.1%), the said result is investigated through OOT and no laboratory error is identified.

Based on above guidance significant change in assay is confirmed, Is it right to start intermediate study in all 3 batches?

As per my view , here no needs to start intermediate condition stability study, we should justify with consultation of Regulatory affairs.

  

HPLC Guard Column: Use & Benefits in Gradient method

In Pharmaceutical Industries Related Substances test analysis is very critical, particularly when the HPLC method analysis is gradient method . To get smooth baseline, no additional peak is always challenge in gradient method analysis.

In such cases Guard column is useful to get smooth baseline and exclusion of any additional peak due to impurity available in solvent which is used in mobile phase and diluents preparation.

"If you have already validated method, then method Equivalency data is required before routine use of Guard column".

What is a guard column?

A guard column is a protective column or cartridge installed between the injector and the analytical column. It serves to remove the impurities and suspended solids from reaching the analytical column. Typically it has a length of about 2 cm and internal diameter of 4.6 mm. Guard columns are packed with pelicullar particles of around 40 μm size to offer negligible pressure drop. 

 The proficient operation of HPLC instrument is dependent on freedom of mobile phase and sample from chemical impurities or solid suspensions. Precaution and handling of use of  mobile phase  discusses measures that should be adopted during preparation and use of mobile phase. Importance of cleaned sample (Centrifuge or filter with syringe filter)  injection is always benefits.

HPLC column is a critical component of the HPLC system which requires careful handling and protection. It is expensive to keep replacing columns frequently so your objective should be to maximize the useful life of the column so that every time you get the desired accuracy and consistency of results.

The chromatographic behavior of the HPLC column begins to decline over use due to gradual accumulation of impurities and suspensions. Particles larger than 2μm present in mobile phase or sample start to deposit on the inlet frit of the column thereby disturbing uniformity of flow. Smaller particles result in increased backpressure so they begin to block the flow path in the stationary phase.

Nature of contaminants:

• Highly retained compounds such as fatty acids in reverse phase separations
• Irreversibly retained compounds like residual proteins which were not removed completely at time of sample extraction. 
• Particulate impurities can result from non filtration of samples, particulates released by wear of system components such as seals in the pump or injector.
• Crystalline deposits resulting from drying of residual buffers inside column. Washing of columns with HPLC grade water after use or buffer solutions prevents such salt deposit formation.

Desirable features of guard columns:

• Guard column should have preferably the same packing as the analytical column to eliminate separation complications
• Internal ID of guard column should be comparable to analytical column to minimize back-pressure. Shorter guard column length is preferable but it should be long enough to prevent strongly retained compounds from reaching the main column
• Frit facing the injector should be removable for cleaning by removal of about 2 mm of material and filling with fresh material
• Disposable cartridge type guard columns are convenient and economical to use compared to refillable guard columns.

Guard columns need to be changed on regular basis but intermediate change becomes necessary through observation of changes in chromatographic behaviour such as increase in backpressure, peak broadening and, changes in retention time of peaks. However, the frequency of change can be decided on the basis of chemical composition of sample, presence of highly retained or irreversibly retained components, injection volume or number of injections.

 

OOS Investigation case study -7 (Instrument error)

OOS Investigation case study-7 (Assay)

OOS observed in Assay test. 

(Single preparation test and duplicate injections from same vial) 

During investigation when you found any root cause in Preliminary or hypothesis testing, before planning of re-analysis, Use any of Investigation tools (5 Why, 6 M etc to rule all other probabilities)Review it thoroughly and plan the negative experiment if required to make the investigation more adequate. 

During investigation when you found any root cause in Preliminary or hypothesis testing, before planning of re-analysis, Use any of Investigation tools (5 Why, 6 M etc to rule all other probabilities)Review it thoroughly and plan the negative experiment if required to make the investigation more adequate. 

Description of Event:
OOS result observed in Assay test.
Result: 97.4% (From same vial Injection-1: 99.8%, Injection-2:94.9%)
-Limit: 95.0 - 105.0%.

Mean result is within specification limit, but one injection result from same vial is 94.9% which is not complying to the specification limit, hence OOS initiated.

Preliminary investigation:
During preliminary investigation checked all possibilities for lower Assay results like Instrument error (No pressure fluctuation , no air bubble in mobile phase/Rinse line ) Calculation error (wrong weight, wrong potency etc.), Standard preparation error (recovery factor of standard and control standard is 99.8%) and all other possible causes for lower result, but no error is identified in preliminary investigation.

During review of pressure graph it was notice that though there is no pressure fluctuation, but at zero time (during injection) subject injection pressure is lower than other all injections pressure (Blank, Standard, control standard and injection-1 of sample (99.8% result).

Zoom pressure graph: (In normal scale graph this pressure difference may not be visible).

Based on above observation there might be possibility that during second injection due lower pressure complete planned volume (20µl) is not drawn by injector.

So to rule the instrument error hypothesis testing should be planned as still we are not sure that which result is true i.e. 99.8% or 94.9% .
Re-measurement:
Hypothesis testing is performed to rule out instrument error, vial filling error, dilution error etc. Hypothesis is planned on different HPLC system and all other things are remain same.
Same vial result is found within specification limit (Mean 99.6%, Injection-1: 99.7%,  Injection-2: 99.5%)
Refilled (100.1%) and re-dilution (99.8%) results are found well with in specification limit. 

Based on outcome of hypothesis , repeat testing/re-analysis can be planned from same aliquot/sample and invalidate the initial OOS result.

Now the question is , 
Why one injection result is lower?, Is this due to low pressure at zero time, If yes, then why lower pressure at zero time in one injection? Is this momentary instrument malfunction? Or any other reason. We have to hand over instrument to service engineer to identify the root cause for low pressure.

Based on service engineer report ,scientific rational and justification we can conclude the OOS with proper CAPA.  

Impact Assessment:

As an Impact assessment we have to evaluate at least last 05 analysis on same instrument and after rectification of error at least 03 analysis.

Human Error

                            HUMAN ERROR

In Pharmaceutical Industries human error and its reduction is very bib challenge.

During regulatory audit most of the investigator asking data of human error trend for OOS/OOT/Deviatrion/Incident and way forward to reduce the human error.

“Human Error is commonly defined as a failure of a planned action to achieve a desired outcome”.

Human error Categories :

Failures of action, or unintentional actions, are classified as   
  1-Skill-based errors: This error type is categorised into--

             A-Slips of action 

             B-Lapses of memory.

         2-Mistakes: Failures in planning are referred  to as mistakes, which are categorised as 

         A:Rule based

         B: knowledge-based

  

Skill-based errors:

Slip of Action tend to occur during highly routine activities, when attention is diverted from a task, either by thoughts or external factors. Generally when these errors occur, the individual has the right knowledge, skills, and experience to do the task properly. The task has probably been performed correctly many times before. Even the most skilled and experienced people are susceptible to this type of error. As tasks become more routine and less novel, they can be performed with less conscious attention – the more familiar a task, the easier it is for the mind to wander. This means that highly experienced people may be more likely to encounter this type of error than those with less experience. This also means that re-training and disciplinary action are not appropriate responses to this type of error.

A memory lapse occurs after the formation of the plan and before execution, while the plan is stored in the brain. This type of error refers to instances of forgetting to do something, losing place in a sequence, or even forgetting the overall plan. 

A slip of action is an unintentional action. This type of error occurs at the point of task execution, and includes skipping or reordering a step in a procedure, performing the right action on the wrong object, or performing the wrong action on the right object.

Slips and lapses can be minimised and mitigated through workplace design, use of checklists, independent checking of completed work, discouraging interruptions, reducing external distractions, and active supervision.

Mistakes:

Mistakes are failures of planning, where a plan is expected to achieve the desired outcome, however due to inexperience or poor information the plan is not appropriate. People with less knowledge and experience may be more likely to experience mistakes. Mistakes are not committed ‘on purpose’; as such, disciplinary action is an inappropriate response to these types of error.  

 Mistakes can be minimised and mitigated through robust competency assurance processes, good quality training, proactive supervision, and a team climate in which co-workers are comfortable observing and challenging each other. 

 Mistakes can be rule-based or knowledge-based.

Rule-based mistakes refer to situations where the use or disregard of a particular rule or set of rules results in an undesired outcome. Some rules that are appropriate for use in one situation will be inappropriate in another.  

Knowledge-based mistakes result from ‘trial and error’. In these cases, insufficient knowledge about how to perform a activity to get a accurate result.

Violation:

Failure to apply a good rule is also known as a violation. Violations are classified as human error when the intentional action does not achieve the desired outcome, or results in unanticipated adverse consequences. Violations tend to be well-intentioned, targeting desired outcomes such as task completion and simplification. 

Note: Violations are classified as human error only when they fail to achieve the desired outcome. Where a violation does achieve the desired outcome, and does not cause any other undesired outcomes, this is not human error. These types of violations may include violation of a bad rule, such as a procedure that, if followed correctly, would give unexpected data. In such cases, a review of the rules and procedures is advisable.