[191 LEC] 1st Exam

Drug Substance

• Substance that elicits pharmacological activity

• Rarely administered alone

• e.g. nifedipine (CCB)

Dosage forms

Physical form of a pharmaceutical formulation containing the drug and some inactive ingredients necessary to prepare it

Drug delivery system

• Specialized dosage forms where one can predict the release of the drug from such systems

• Either delayed or extended release properties

  • Immediate vs Modified

    • Modified-release Types

      • Extended Release (Official Term)

        • Controlled release (non-official)

        • Sustained release (non-official)

      • Delayed-release (official term)

        • Enteric-coated (non-official)

        • Gastro-resistant (non-official)

Why do we develop drug delivery systems?

• Formulation Issues

• Physicochemcial issues of bioactive compounds

How do we develop a pharmaceutical product

• Pre-clinical -> IND application (to be able to thru clinical testing)

  • Preformulation

  • Synthesis

  • Toxicology

  • Initial Formulation

  • Method Development and validation

  • Stability and degradation studies

• Clinical -> NDA (needed for commercialization)

  • Formulation modification

  • Final formulation

  • Method development and validation

  • Stability and degradation studies

  • Extractables/Lechables

  • Manufacturer validation

• Post Marketing

  • Production risk mitigation

  • Counterfeit analysis

  • Failure analysis

  • Post approval changes

• Formulation development

  • Laboratory scale: 1-2kg

  • Quality control parameters

• Pilot batch

  • 10% of the commercial scale or 100,000 units (whichever is greater)

  • Stability (Accelerated and long-term)

  • Validation (Process, Cleaning, Analytical)

• Commercial batch

  • Acquisition and control of materials

  • Provision of facilities, utilities, and equipment

  • Production (including packaging and labeling)

  • Quality control and assurance

  • Release

  • Storage

How do we plan our experiments?

1st Step	2nd Step
Physicochemical Factors	Risk assessments, Literature review, Preliminary experiments
Formulation Factors
Physiologic Factors

How do we execute our experiments?

1st Step	2nd Step
Physicochemical Factors API Excipients	Preformulation
Formulation Factors Materials attributes Process parameters	Screening & optimization
Physiologic Factors Targeted site	In silico, in chemico, in vitro, in vivo

Product Lifecycle

• Pharmaceutical Development

  • Drug substance development

  • Formulation development (including container/closure system)

  • Manufacture of investigational products

  • Delivery system development

  • Manufacturing process development and scale-ip

  • Analytical method development

• Technology Transfer

  • New product transfers during development through manufacturing

  • Transfers within or between manufacturing and testing sites for marketed products

• Commercial Manufacturing

  • Acquisition and control of materials

  • Provision of facilities, utilities, and equipment

  • Production (including packaging and labeling)

  • Quality control and assurance

  • Release

  • Storage

  • Distribution

• Product Discontinuation

  • Retention of documentation

  • Sample retention

  • Continued product assessment and reporting

QbD

• systematic, risk-based, scientific approach to the development and quality management of pharmaceutical products

• A paradigm shift away from end product testing to real time monitoring 

• Intended to build  drug substances product components and dosage forms through comprehensive understanding and monitoring of the evolving 

• Receiving clearance to conduct clinical studies or gaining market approval is not contingent upon the use of QbD

• QbD is not a regulatory expectation for all situations but rather a unique set of principles that can be applied to science based pharmaceutical product and process development

QbT vs QbD

Quality by Testing	Quality by Design
At  every step, there is quality control testing  E.g. For Granules, the following IPQC are conducted: Compressibility Index Hausner Ratio Particle Size Tablets: Disintegration, Friability, Assay, Hardness, Thickness, etc.	Product and process understanding and control based on sound science and quality risk management
Quality control tests do not improve the quality of the product -> only checks quality E.g. in using mixing tank, we only get samples and assess the product	E.g. in using the mixing tank, … E.g. in production of effervescent tablets, <20% humidity must be ensured → measures are put in place to ensure critical factors are within the ideal range

Design of experiments

• Screening method involving factors that can affect the final product to find the most influential factor

  • Rank CQA and CPA in order of importance

  • Involves statistical tests

  • Screening Designs:

    • Factorial

    • Fractional Factorial

  • In tablet making, the following CQA are considered:

    • Lactose -> Lubricant

      • Amount

      • Particle size distribution

  • Can we obtain an optimal product using screening? No.

  • We need to proceed to optimization

• Optimization designs

  • Central Composite Design

  • Box-Behnken Design

• We use statistics to develop our product in the most objective way possible

  • Avoids bias

Elements of QbD

• Quality Target Product Profile

  • Intended use in a clinical setting, route of administration, dosage from, and delivery system(s), dosage strength, container closure system, release, stability (CQAs) 

•  Product and Process Design

  • Product Design: characteristics of drug substance, excipients (CMAs)

    • Process Design: unit operations (CPPs)

•  Control strategy

  • End product testing -> real time testing

  • Avoid end product testing since it does not ensure product of quality

    • Real time testing is preferred.

• Process Capability and Continual Improvement

  • Ensure that any deviations are corrected before they result in defects

  • Finds out if process is capable

Pharmaceutical QbD Tools

• Prior Knowledge 

  • Stems from previous experience that is not available in the literature

    • E.g. We try procedures from literature then if it doesn’t work, we adjust them

  • May be proprietary information, understanding, or skill that applicants acquire through previous studies

• Risk Assessment

  • To identify potentially high-risk formulation and process variables that could impact the quality of the drug product

    • E.g. ishikawa diagram

• Mechanistic Model, Design of Experiments, and Data Analysis

  • Reveals relationships between input factors and output responses and uncover how factors jointly affect the output responses

  • Formal way of maximizing information gained while minimizing information gained while minimizing the resources required

  • Identify optimal conditions and design space

•  Process analytical technology

  • Provide continuous monitoring of CPPs, CMAs, or CQAs to make go/no go decisions and to demonstrate that the process is maintained in the design space

    • Examples use of infrared technology

Principles of DoE

• Component of QbD

• Systematic and simultaneous evaluation of variables (material or process) to develop a product with the desired quality attributes and uses statistics to ensure that the conclusions are valid

• End goal is to obtain the optimal experimental conditions

• Results in a robust scale-up process

• When does a material attribute or process become critical?

  • Risk-assessment -> ranking

  • Experimentation -> determine response

  • Statistical analysis → determine if factor is critical

•  How do you conduct statistical analysis

  •  In a battery of tests, not all will have ideal results

  •  

• Advantage of DOE make a polynomial equation

  • Allows prediction of factors that are critical for the product and understanding of the magnitude of such effect 

  • Developing an optimum product requires scaling up and predictability of factors that could affect it

• Design space or legion of interest or experimental domain

  • experimental  field that must be investigated; it is defined as the minimum and maximum limits of the variables being studied

• Factors or independent variables

  • Experimental factors that can be changed independently from each other

  • Material attributes and process parameters

  • Levels

    • Different values a factor can assume based on the design space

• Response or dependent variables

  • Observed or measured values or the results of the experiment

  • Quality attributes

Traditional Method vs DoE

Traditional Method	DOE
One-factor-at-a-time (OFAT) or single factor experiments Part of preliminary experiment OFAT is better than trial-and-error and preliminary experiments	Simultaneous evaluation of the impact of factors (material attributes and process parameters) on the responses (quality attributes)
Carried out by monitoring the effect of one factor at a time on an experimental response while keeping the other factors constant	Most objective way to analyze the relationship of factors and responses -> uses statistical tools
	Screening, characterization, and optimization

Steps to set up DoE

1. Define the objectives

2. Identify the response and factors (and levels to study)

3. Identify the experimental design

4. Conduct the experiments

   1. Conduct it using the optimum conditions

5. Evaluate the experimental data

   1. e.g. software will validate if polynomial equation is valid

6. Confirm the models

NOTE:

• Pwede magkasama ang CPP at CMA 

• Pwede na qualitative yung data (e.g. type of crosslinker)

• DoE will not necessarily produce the best product

  • You prioritize a goal then the DOE provides a balanced formulation (optimal)

  • Example DOE goals:

    • Maximum percent yield

    • Minimum particle size

    • Maximum drug entrapment efficiency 

  • Lower particle size means lower drug entrapment hence the need for optimization

When does a quality attribute become critical?

Criticality is identified via risk assessment and is product-specific

CMA vs MA

• Material Attribute (critical & noncritical)

  • Physical, chemical, biological, or microbiological property or characteristic of a drug substance or excipient that should be within an appropriate limit, range, or distribution to ensure the desired quality of that drug substance, excipient, or in-process material.

• Critical Material Attribute

  • Material attribute that warrants further study

  • A material attribute is critical when a realistic change in that material attribute can have a significant impact on the quality of the output material

CPP vs PP

• Process Parameters (Critical & noncritical)

  • Refers to the input operating parameters (e.g. speed and flow rate) or process state variables (e.g. temperature and pressure of a process step or unit operation.

    • E.g. stirring speed, stirring time, rate of cross-linker addition, etc.

• Critical Process Parameters

  • A process parameter is critical when its variability has an impact on a critical quality attribute and therefore should be monitored or controlled to ensure the process produces the desired quality

    • E.g. rate of cross-linker addition, stirring time

QA vs CQA

• Quality Attribute (Quality Attribute)

  • Physical, chemical, & biological or microbiological property or characteristic of an output material including finished drug product that should be within an appropriate limit, range, or distribution to ensure the desired product quality

    • E.g. identify, morphology, particle size, etc.

• Critical Quality Attribute

  • Based upon the severity of harm to the patient should the product fall outside the acceptable range for that attribute

    • E.g. particle size, yield, entrapment efficiency

DoE

Define the overall goals of DOE

• Selecting responses

  • Choose the critical quality attributes of microparticles

  • Ask subject matter experts and brainstorm

• Selecting factors

  • What factors will affect the response(s)?

    • The factors should affect ALL the responses. Remember, in a polynomial equation all factors will always be present.

  • What factors will affect the yield, size, and EE of the microparticles?

    • Based on an exhaustive review of literature

    • Risk assessment

    • Preliminary experiments

FMEA vs Fish Bone

Fishbone

• Categories can change

• E.g. factors include environment, human , instruments, materials, and process

Selecting Levels of Each Factor

• Know how to make a bad product to know how to make a good product

• Ensure that levels are far enough apart to create a change in the response, but not too far that you stop making the product