It had to. Six Sigma strives to reduce variation in products and processes, while Lean manufacturing goes for ending manufacturing waste.  It is clear that there are several areas within the pharmaceutical industry where these two could be implemented, and are strongly advised by expert pharmaceutical consultants:

-Research and Development (R&D).  This is the principal process where the business starts for all pharmaceutical companies, and it is also the most expensive one.  Lean manufacturing comes into the picture to understand and define the critical procedures for developing new drugs, as well as to analyze and guide the current ones.  In this way, pharmaceutical companies are trying to reduce drug failures, learn to utilize resources to the maximum, increase productivity, and apply effective criteria to use personnel and other resources efficiently.

-Cycle times.  Cycle times for pharmaceutical procedures are extensive, and these are affecting on-time manufacture, supply, and launch of new products.  Timing is critical for the success of a new drug, thus, companies must reduce production timings to take full advantage of the market.  Lean manufacturing and Six Sigma offer value stream mapping and process modeling concepts capable of reducing these cycles and costs, making the processes and staff, more efficient.

-Defects.  These are a huge risk for pharmaceutical companies.  No one wants to risk making people ill or to cause a death.  Lean’s DFSS uses scientific and statistical tools which reduce the cost of human mistakes and inefficiencies.

Six Sigma creates many opportunities for pharmaceutical companies using it. While Lean happens at the operations and management levels, applies to the behaviors towards customer focus and coherent mission statements and values, Six Sigma’s goal is to change the organization’s momentum.

A broad strategy towards Six Sigma training is required during several stages of the change to Lean manufacturing, in order to gain stronger organizational skills at the management and general staff levels.

IT is vital in the transitioning process to ensure constant improvement.  The complexity of the manufacturing processes makes it necessary to acquire flexible and practical IT systems.  Data gathering and analysis must occur fast, effectively, and accurately; improving reliability.

The reliability aspect makes this information the basis for guiding, decision-making, and cost lowering.  Over time, an automatic system will make quality results possible, speeding analysis and design changes to improve the operation’s efficiency and compliance.

By being able to meet the demands in real time, inventories and costs are reduced efficiently before the drugs’ expiration dates.

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The Pharma industry is facing extreme change.  Gone are the days when pharmaceutical manufacturers made million in profits no matter the times.  Today’s challenges are transmuting the field’s reality for the future: expiration of blockbuster drug patents, a decreasing pipeline of blockbuster drugs, pressure from generics, doubt about the future of healthcare compensation, mergers and acquisitions.

This somber panorama is moving Pharmas to evaluate the best ways to combine and manage themselves while urging external organizations to do the same in order to continue being competitive.

To maximize their profits, Pharmas are scanning their activities to achieve optimization, efficiency, and quality amid the crisis.  Manufacturing is in this scope, as companies try to lower costs throughout every area, prompting bold manufacturers to expand their Lean Six Sigma enterprises with predictive modeling techniques, to earn new perception, and encourage change within the organization.

For many years, the Pharma industry has been characterized for being delayed in manufacturing efficiency and productivity, specially because it is very expensive and involves a great deal of work to comply with regulatory principles, which call for revalidation of processes after a change.  This has established a road of inefficiency, waste, and lack of quality control.

Until now, pharmaceutical manufacturers had not had any economic motivators to support change, and now they face the consequences.  Luckily, in recent years, they have received some support from the FDA and other regulatory bodies, which recognize the lack of efficiency and quality control and have backed up a “quality by design” model to substitute the previous one of “quality by test results”.

The FDA has established the Process Analytical Technology (PAT) initiative, which aims at guiding pharmaceutical manufacturers towards consistent, predictable, and higher quality levels.  By accepting PAT, Pharmas are changing their focus to two management approaches: Lean manufacturing and Six Sigma, with the intention of reducing waste to meet customer demand and market changes, and to lessen the variation in products and processes, to avoid product defects.

Lean and Six Sigma are powerful tools to improve quality, compliance, productivity, costs, and speed, allowing for the Pharma to provide better products in a cheaper and faster way.

But it doesn’t stop there.  To effectively leverage PAT and Six Sigma, pharmaceutical manufacturers must use modeling tools that improve quality even before a product is manufactured.  They require predictive analysis that gives them information about the impact of numerous changes, in ingredients or processes, on the quality of the end product.  The Monte Carlo simulations is such a tool.  It uses probability distributions as process inputs, instead of one value.

In this way, pharmaceutical manufacturers can predict the quality of a product more accurately, thus, balancing the quality demands of Six Sigma against Lean principles, that aims to manufacture products faster and cheaper.  It may also help in predicting manufacturing demand and cycle periods, as well as the critical steps to achieve the best quality.

Imagine the improvement over current practices of testing quality once the manufacturing process is over!  To get started, research thoroughly the Monte Carlo model and even ask pharmaceutical consulting firms for detailed information on its implementation.

Embracing change today is the way to flourish.  New methods like Lean Six Sigma, supported by prediction tools, clear the path towards a better future and a better company, all for the common good.