Concept wise Quality-by-Design or QbD is not new. The word quality-by-design was introduced by Juran in his work on quality management. And since then organizations have used QbD to introduce quality aspect into products and services.
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However, in my view QbD is a holistic concept for business improvement and has not been fully explored to its full potential. It can do much more than just build-in quality. In the video below, I have touched upon how QbD can improve business resilience. Watch on…

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• How to cut costs strategically using Kaizen
• Quality-by-Design (QbD) approach means Design for Manufacturing (DFM)
  
• Business Turnaround and Continuous Improvement Tips & Tricks Part 5 of 6: TQM in a Nutshell
  

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#Qualitybydesign #Businessresilience #Juran #QualityManagement #AgileKaizen #DesignThinking #DesignSpace #ProductDevelopment #QbD #BusinessTransformation

Lean Innovation, Hoshin Kanrii and Six Sigma (DFSS- design for six sigma) for product design, development and manufacture via 3D Printing (i.e. Additive Manufacturing) Case Study by Dr. Shruti Bhat, gives benefits of applying Hoshin Kanrii, DFSS and Lean Innovation techniques to a drug product design, development and manufacture via 3D Printing.

The study findings however can be extended to product development across other industry verticals.

Some of the benefits of applying continuous improvement methodologies such as Lean, Hoshin Kanrii and Six Sigma to research and product development include-
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1. Application of Hoshin Kanrii and DFSS along with Quality-by-Design (QbD) to product development usually brings novelty in product features, process characteristics and/or product utility, thus favors patenting and generation of additional revenues.
2. While, Lean Innovation creates products with effective and efficient production and packaging processes, with no scope for ‘rework’ thus, better Operations Management.

​The study uses Isosorbide dinitrate (ISDN) as model drug, although other drugs can also be used in this therapeutic platform.

2x3 Factorial Design of Experimentation (DOE) was used to design drug beads. The results were evaluated for regression analysis, Main and interaction effects of parameters, Contrast Column Dispersion effects, Normal Probability Plots, Pareto and Process Capability Analysis.

The drug beads were further used as ‘starter’ seeds to develop MUPS (multi-unit particulate system) anti-angina ‘rate-programmed’ drug product.

The pharmacokinetic- pharmacodynamic (PK-PD) modeling was done using Doebrinska- Welling equation. MUPS were developed using 3D Printing technology via a 12- Run Plackett Burman DOE.

All hardware, software applications involved in the study were pre-validated. All qualifications i.e. Design Qualification (DQ), Installation Qualification (IQ),  Operational Qualification (OQ), Performance Qualification (PQ) for each experimental run was done as per USFDA guidelines. Data was analysed statistically using Paired ‘t’ test. Reliability Testing was conducted as per ICH current Good Clinical Practices (cGCP) guidelines.

Product prototype and Reference listed drug (RLD) were compared for bioequivalence compliance. The prototype is ready for commercialization.

This study also gives benefits of using 3D Printing technique for pharmaceuticals and how the technique can be applied to product development across other industry verticals!
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For details on how to apply Lean Innovation, Hoshin Kanrii and DFSS to product design, development and manufacture, watch the video …

To learn more about how Shruti can help your organization achieve new heights or to book a Workshop, Contact Dr. Shruti Bhat via Form or WhatsApp

1. Workshops & Online Courses for Pharmaceutical Research and Drug Product Development by Dr. Shruti Bhat
2. Kaizen for Cost-Savings and Organizational Excellence
3. Mistake-Proofing Pharmaceutical Products: What can we learn from Valsartan, Losartan and Irbesartan recalls?
4. How to develop a culture of ‘Continuous Improvement’ in an organization?
5. ​Innovation is not an initiative. It’s a business process !​

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#ContinuousImprovement   #Innovation  #Lean  #HoshinKanri  #DFSS  #DesignForSixSigma

Conceptual data modeling refers to a summary type of information modeling that is typically used for projects regarding data and strategies. It often relates to the organization as a whole. It is known as conceptual data modeling since its nature is quite abstract. The typical aspects of conceptual data modeling cover all aspects of an organization including the product, location, customer, retail and more. It is meant for implementation and use with a business audience. 
  
This type of data modeling has a wide selection of concepts that are applied to different organizations, as it is best suited. There are 20 to 50 different concepts that all have their own adjustable characteristics. Each concept has its own standards and is applied to organizations depending on how it is best suited. Conceptual data modeling is frequently used during the beginning stage of planning. It is a vital stage in creating a data model that accurately represents an organization’s business.  
  
Conceptual data modeling envisages the entire arrangement of an organization’s database and gives information regarding the configurations of data and subject capacities within an organization. The implementation of conceptual data modeling begins with focusing on the key subject points of the organization. After which all main articles within each subject point can be discussed in greater detail. 
  
It embraces all types of entities and associations. The use of symbolic representations allows for visual associations between the subject points and the associations between each entity within a subject point. These relationships can vary from one on one, one to several and various connections between the articles. The structures of data that are used in conceptual data modeling are ones that have not already been used in the organization’s database. 
  
The model is formed by collecting business necessities from a variety of sources such as documentation, team feedback, analysts, experts and those who deal with database reporting. Data modellers are the key players in conceptual data modeling since they select the type of model to use and pass on the model to the organization for inspection and application. The team discussion aims to create a comprehensive data model. 
  
An example of how a conceptual data model would work would be to focus on the different key aspects of the organizations. Once the key aspects are clear, the model can provide inspiration for the team to come up with ideas that can help offer insight into ways in which the requirements of each aspect can be met. 
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Business process effectiveness is the result of a well-made business process that increases customer satisfaction and value. It is necessary for business processes to be effective in order for the company to grow since customer value is such an important aspect of the majority of organizations. A successful way to increase business process effectiveness to a company is to add greater focus on daily business activities and figure out how they can be made more effective, which slightly differs from efficiency.  
 
It is necessary to develop a good strategy in order to increase the success of an organization. Even if a good strategy is developed, it does not mean much until it has been applied effectively. If a business is lacking in business processes, it will show by wasting money and time, which tends to be noticeable by less-than-favorable quality in products or services. It can also cause employees to lose their motivation and loyalty to an organization. It is ideal to improve the business process in order to ensure this does not happen.
 
The main ideas behind business process effectiveness include finding out what the customer and the business focus on and what is of importance, identifying the current main business processes, prioritizing various processes and allowing employees to contribute. Employees should be educated on the ideas behind new business processes that are being implemented in order to ensure that the effectiveness is highly possible. Employees in all departments need to be able to communicate freely and to be heard on various topics, such as their ideas regarding inadequacies or areas that are lacking within the organization. 
  
It is not always essential for organizations to undergo a complete make over since increasing effectiveness can be done in increments. If an organization is experiencing negative effects from current processes then it is essential to find a new way of making things work. The first step to improvement is mapping out and detailing the various stages in each process. The map must then be analyzed and questioned in order to find out the root cause of the problem. It is highly likely for the problem to arise again if the root cause isn’t discovered. 
 
The next stage requires a redesign of existing processes by getting rid of the identified problems. Once the problems are ridden, the new process has to be backed up by the appropriate resources. Implementing new business processes can be a large step and requires a lot of communication and sometimes retraining as well. After all stages are complete, it is vital to review the changes and to continue to use the new business process in order to achieve greater effectiveness. 

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Root cause analysis makes it easier to identify the reason a problem occurred in order to prevent it from reoccurring. It is essential to identify the underlying root cause of the problem, which are controllable through management and open up the possibility to recommendations to be made. Root-cause analysis is also a decision-making tool, very helpful to business leaders to take strategic decisions based on facts.

Root cause analysis requires the collection of data, identification of the root cause, charting of information regarding the cause and suggestions for making changes and implementing them.

There are different methods for root cause analysis and some are better at pinpointing the actual root cause. Different techniques apply to different circumstances. 
 
There are three vital steps in order to perform a root cause analysis. The steps include- 
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1. Defining the problem and its affect on goals.
2. Analyzing the root causes through visual representation via mapping and
3. Preventing unsatisfactory impacts by choosing the solutions that are effective.

Defining in stage one asks, “What is the problem?” Analyzing in stage two asks, “Why did it happen?” Whilst stage three, or preventing, asks, “What will be done?”
 
A root cause map is constructed during a root cause analysis in order to determine the reason for an incident’s occurrence in a visual manner. It links the various relationships in order to come up with potential causes.  The relationships that are considered are cause and effect types. It is meant to be a simple map, however some situations require much more detailed maps. 

A root cause map begins on the right hand side by stating the problem. The map then involves arrows that point viewers into the direction of causes, which are then asked “Why” for each. Each time the question is asked, the response is added to the right of the respective boxes. The questions continue five times until the root cause of the problem is clearly identifiable. The reason that this works is because it is easy to see when the optimal state of processes has been sacrificed or altered. 
 
The root-cause diagram is also known as Ishikawa Diagram or Fishbone Diagram. It is one of the most commonly used tools for cause-and-effect explanations. Other variations of graphs and diagrams can be used to depict root cause analysis as well.

Brainstorming, ideation and mind-mapping are some of the best ways to come up with solutions once the cause has been determined. Once the analysis is complete, the information should be shared in order for others to understand the root cause of an issue. The root-cause analysis sharing may be done via A3-reporting.



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