High-Fidelity PCR Reagents Continue to Propel DNA Research with Unparalleled Accuracy and Speed

New proprietary tracking dyes within high-fidelity DNA polymerase and qPCR master mixes facilitate easier, more accurate PCR set-up for researchers.  The Thermo Scientific Phusion Green High-Fidelity DNA Polymerase and Luminaris Color qPCR master mixes utilize proprietary tracking dyes to speed up the pipetting process. By providing a visual confirmation, the mixes are designed to vastly reduce the chance of human error, while also decreasing the number of procedural steps required. Most importantly, the dyes have been engineered not to interfere with the reaction or any downstream applications.

These new Phusion and Luminaris products form the latest additions to the renowned Thermo Scientific Phusion High-Fidelity DNA Polymerase family. First launched a decade ago, the Phusion High-Fidelity DNA Polymerase was the first DNA polymerase, developed using fusion protein technology to provide a combination of accuracy and speed previously unattainable using conventional enzymes.  Known for performance with all major PCR applications, the Phusion technology has played a central role in helping researchers accomplish an array of key scientific achievements, including the creation of the first functional synthetic genome.

“Phusion Polymerase technology has dramatically increased the productivity of labs running PCR,” says Margarita Leckiene, Director of Nucleic Acid Detection & Molecular Tools for Thermo Fisher Scientific. “Our philosophy is to simplify customer workflows further and increase the reproducibility of results. We are constantly working to further advance the accuracy and robustness of Phusion polymerase including the most recent innovation of special enzyme formulations that are optimized for NGS applications, offering equal amplification efficiency across entire genomes.”

This technology, coupled with Thermo Scientific PCR instruments and accessories such as theThermo Scientific Arktik Thermal Cycler and Thermo Scientific Piko Plate Illuminator, provides an efficient integrated solution that delivers

• DNA amplification with extreme accuracy
• Enhanced visual control
• Significantly shorter protocol times.

To recognize the impact of the original Phusion polymerase and a subsequent decade of innovation in this area, Thermo Fisher has launched Phusion Fest, an interactive campaign celebrating the importance of PCR in the laboratory. Phusion Fest encompasses a fun, scientific trivia game, special offers across a variety of molecular biology products and free samples of selected Phusion products.  More information on Phusion Polymerases and the Phusion Fest can be found by visitingwww.thermoscientific.com/phusion.

World’s Pharmaceutical Development Manufacturing Base Moving to India

The India Brand Equity Foundation (IBEF) has compiled its findings and released an overview of the current generics market in India. They predict that the Indian pharma market is now at the precipice of the next stage in its development, having seen manufacturing innovation and development technologies rise- thanks to the explosion in generics production.

During the last 3 years, exports of pharmaceuticals (largely generics) have grown at over 21.5% (CAGR) and now accounts for over $13bn in annual sales. Highlighting India’s dominance, nearly 40% of Abbreviated New Drug Applications (ANDA) received by the FDA in 2012 were from India, with a further 87 confirmed and another 25 already received between January and June 2013.

This huge growth in generics production has seen the country become a hotbed of manufacturing innovation – India has over 3000 DMFs registered with USFDA – which coupled with increased investments in R&D means India is now ready to challenge traditional big pharma and start producing more patented products. A natural evolution of the success of the generics market has been the rise in supergenerics across India where much R&D spend is currently being invested (e.g. Lincoln Pharma’s patent for NDDS).

With the world’s pharmaceutical development manufacturing base moving to India – there are 546 USFDA approved company sites (second only to the US), 23 companies holding 1100 authorizations with UK’s MHRA, and 166 companies with CEPs (Certificates of Suitability) from EDQM – coupled with the rise in supergenerics, the country’s next natural step is to use its world leading development expertise in the creation of new chemical entities.

Recognising this opportunity, the Government of India is putting in place supportive initiatives with the goal of cementing the country’s position as the ‘pharmacy of the world’ and creating a global innovation hub. With generics predicted to rise to 35% of global pharmaceutical market value by 2016 (some $400bn+), and with an annual growth rate of 27% amongst Indian generics exports (comparing very favourably with the global average of 10%) the Government and Pharmexcil are forecasting much of this revenue will be reinvested across the country in new research- leading to a steady pipeline of future drug targets.

In support of this, the Indian Government has committed to three schemes including a major multi-billion dollar initiative with 50% public funding through a public-private partnership (PPP) model to harness India’s innovation capability. In addition, the Government has made tax-breaks available to the pharmaceutical sector and a weighted tax deduction of 150% for any R&D expenditure incurred. Additionally, they have also introduced 19 dedicated Special Economic Zones to help stimulate pharma sector investment across the country.

Steps have also been taken to streamline procedures covering development of new drug molecules and clinical research- including two schemes ‘New Millennium Indian Technology Leadership Initiative’ and the ‘Drugs and Pharmaceuticals Research Programme’, which has been specially targeted at drugs and pharmaceutical research.

Already this year, India’s Dr. Reddy’s, Lupin Labs, Sun Pharma, Ranbaxy and Cipla have invested over $500million in R&D, which is allowing increased innovation in manufacturing processes  and will ultimately help to lower the cost of medicines production.

“India, termed as the Pharmacy of the World, has a basket of wide spectrum of generics that are second to none in terms of quality. The industry is on the track to expand its reach to newer markets, which makes it equally critical for the Indian pharmaceutical industry to keep its focus on quality, affordability and accessibility of medical solutions for the global pharma market. The country’s success in generics manufacturing is helping to keep our industry at the forefront of innovation and over the next few years we are lending our support to the R&D effort across the country so that we are leading in generics production and even developing new drugs out of India” said Mr Rajeev Kher, Additional Secretary, Department of Commerce, Ministry of Commerce and Industry, Government of India.

“Being a world leader in generics, India already has a huge presence in the highly regulated markets in terms of pharma exports. Almost two thirds of Indian generic exports are to the highly regulated markets (e.g. the US and Europe), which speaks volumes about the quality of Indian medicines. The Government of India is supporting Brand India Pharma campaign to reiterate that the Indian pharma market offers credible, affordable and sustainable healthcare solutions” said Dr P.V. Appaji, Director General, Pharmexcil.

About IBEF: India Brand Equity Foundation (IBEF) is a Trust established by the Department of Commerce, Ministry of Commerce and Industry, Government of India. IBEF’s primary objective is to promote and create international awareness of the Made in India label in markets overseas and to facilitate dissemination of knowledge of Indian products and services. Towards this objective, IBEF works closely with stakeholders across government and industry.

FDA Approves Two Drugs, Companion Diagnostic Test for Advanced Skin Cancer

The U.S. Food and Drug Administration today approved two new drugs,Tafinlar (dabrafenib) and Mekinist (trametinib), for patients with advanced (metastatic) or unresectable (cannot be removed by surgery) melanoma, the most dangerous type of skin cancer.

Melanoma is the leading cause of death from skin disease. The National Cancer Institute estimates 76,690 Americans will be diagnosed with melanoma and 9,480 will die from the disease in 2013.

Tafinlar, a BRAF inhibitor, is approved to treat patients with melanoma whose tumors express the BRAF V600E gene mutation. Mekinist, a MEK inhibitor, is approved to treat patients whose tumors express the BRAF V600E or V600K gene mutations. Approximately half of melanomas arising in the skin have a BRAF gene mutation. Tafinlar and Mekinist are being approved as single agents, not as a combination treatment.

The FDA approved Tafinlar and Mekinist with a genetic test called the THxID BRAF test, a companion diagnostic that will help determine if a patient’s melanoma cells have the V600E or V600K mutation in the BRAF gene.

“Advancements in our understanding of the biological pathways of a disease have allowed for the development of Tafinlar and Mekinist, the third and fourth drugs the FDA has approved for treating metastatic melanoma in the past two years,” said Richard Pazdur, M.D., director of the Office of Hematology and Oncology Products in the FDA’s Center for Drug Evaluation and Research.

Zelboraf (vemurafenib) and Yervoy (ipilimumab) were approved in 2011 for the treatment of metastatic or unresectable melanoma.

“The co-approval of Tafinlar and Mekinist and the second companion diagnostic for BRAF mutation detection demonstrates the commitment of pharmaceutical and diagnostic partners to develop products that detect and target the molecular drivers of cancer,” said Alberto Gutierrez, Ph.D., director of the Office of In Vitro Diagnostic Devices and Radiological Health in the FDA’s Center for Devices and Radiological Health.

The FDA’s approval of the THxID BRAF test is based on data from clinical studies that support the Tafinlar and Mekinist approvals. Samples of patients’ melanoma tissue were collected to test for the mutation.

Tafinlar was studied in 250 patients with BRAF V600E gene mutation-positive metastatic or unresectable melanoma. Patients were randomly assigned to receive Tafinlar or the chemotherapy drug dacarbazine. Patients who took Tafinlar had a delay in tumor growth that was 2.4 months later than those receiving dacarbazine.

The most serious side effects reported in patients receiving Tafinlar included an increased risk of skin cancer (cutaneous squamous cell carcinoma), fevers that may be complicated by hypotension (low blood pressure), severe rigors (shaking chills), dehydration, kidney failure and increased blood sugar levels requiring changes in diabetes medication or the need to start medicines to control diabetes.

The most common side effects reported in patients receiving Tafinlar included thickening of the skin (hyperkeratosis), headache, fever, joint pain, non-cancerous skin tumors, hair loss and hand-foot syndrome.

Mekinist was studied in 322 patients with metastatic or unresectable melanoma with the BRAF V600E or V600K gene mutation. Patients were randomly assigned to receive either Mekinist or chemotherapy. Patients receiving Mekinist had a delay in tumor growth that was 3.3 months later than those on chemotherapy. Patients who previously used Tafinlar or other inhibitors of BRAF did not appear to benefit from Mekinist.

The most serious side effects reported in patients receiving Mekinist included heart failure, lung inflammation, skin infections and loss of vision. Common side effects included rash, diarrhea, tissue swelling (peripheral edema) and skin breakouts that resemble acne.

Women of child bearing years should be advised that Tafinlar and Mekinist carry the potential to cause fetal harm. Men and women should also be advised that Tafinlar and Mekinist carry the potential to cause infertility.

Tafinlar and Mekinist are marketed by GlaxoSmithKline, based in Research Triangle Park, N.C. The THxID BRAF Kit is manufactured by bioMérieux of Grenoble, France. Yervoy is marketed by New York City-based Bristol-Myers Squibb, and Zelboraf is marketed by South San Francisco-based Genentech, a member of the Roche Group.

Cancer Research UK installs Flexicon FP50

Cancer Research UK Biotherapeutics Development Unit (BDU) has installed a Flexicon FP50 tabletop filling and stoppering machine from Watson Marlow Pumps Group

A Flexicon FP50 tabletop filling and stoppering machine from Watson-Marlow Pumps Group has automated a previously manual process at a Cancer Research UK facility in Hertfordshire, UK. The FP50 is delivering increased speed and reliability into this critical operation, as well as enhanced vial filling accuracy.

The Cancer Research UK Biotherapeutics Development Unit (BDU) was built in 2010 at South Mimms. It is a modern, MHRA licensed, fully cGMP-compliant, 2000m²facility that is engaged in the process development and GMP production of Investigational Medicinal Products (IMPs) for Phase I clinical trials sponsored by Cancer Research UK.

Recent challenges at the BDU included the introduction of an automated filling and stoppering procedure, which was previously performed manually using a dosing pump. This method was not only labour-intensive and slowed down throughput, but was also unsatisfactory for such a leading edge facility. A reliable automated vial filling process was therefore required for the delivery of future BDU projects.

‘To help deliver this we set out to source a machine capable of rapid, repeatable filling but without any compromise to process quality and control,’ said Tim Hillyer, Senior Scientific Officer at the BDU.

The flexibility offered by the FP50 was ideal for our purposes

The Flexicon FP50 tabletop filling and stoppering machine from Flexicon Liquid Filling, part of the Watson-Marlow Pumps Group, is capable of filling up to 25 vials a minute (up to 100ml capacity). It also offers quick and easy changeover between batches.

‘As a multi-product facility producing small batch size, high-value IMPs, the flexibility offered by the FP50 was ideal for our purposes,’ said Hillyer. ‘Our most recent batches involved not more than a few litres in quantity so having a reliable method for product filling and stoppering enables us to bring new drugs into the clinic in a controlled and reproducible manner.’

Hillyer said the FP50 is quicker than the old manual process by a ratio of several factors. It is also easy to adapt for different vial and stopper sizes. An adjustable walking beam transports vials from the feeding turntable to the different working positions (filling needle and stopper plug) and only two parts need to be changed to cater for the entire range of vials and stopper sizes used by the BDU. The pump is also accurate, allowing the BDU to control the dose volume going into each vial.

The FP50 unit is fully contained within a six-glove isolator allowing the unit to gas the equipment prior to each product fill using hydrogen peroxide vapour. This containment twinned with the speed and efficiency of the FP50 greatly reduces the chances of batch contamination.

The Flexicon FP50 is a universal and aseptic tabletop filling system with integrated full or partial stoppering of rubber stoppers for use in pharmaceutical R&D departments and biopharma facilities. All materials and surfaces are designed to meet cGMP standards for aseptic filling, thus providing a ready-to-use validated filling system to carry out clinical trials and small batch production. The filling accuracy of the peristaltic filling system is better than ±1%.

The operator interface is an easy-to-clean touch screen and keypad. The panel is mounted on a separate control box, remote from the filling unit. This allows the control panel to be placed outside the LAF bench or isolator. It is possible to store up to 20 sets of filling parameters as complete working programmes.

Novartis Japan Achieves Primary Endpoint In HER2 Positive Advanced Breast Cancer Phase III Afinitor Trials

Everolimus

Novartis announced it achieved its primary endpoint of significantly extending progression-free survival with Afinitor (everolimus) in Phase III trials of patients with HER2 positive advanced breast cancer.

Everolimus (RAD-001) is the 40-O-(2-hydroxyethyl) derivative of sirolimus and works similarly to sirolimus as an inhibitor of mammalian target of rapamycin (mTOR).

It is currently used as an immunosuppressant to prevent rejection of organ transplants and treatment of renal cell cancer and other tumours. Much research has also been conducted on everolimus and other mTOR inhibitors for use in a number of cancers.

It is marketed by Novartis under the tradenames Zortress (USA) and Certican (Europe and other countries) in transplantation medicine, and Afinitor in oncology.

Process Validation Guidance: A Bad Fit for Aseptic Processing?

When he first assessed FDA’s draft Process Validation guidance a few years ago, consultant James Agalloco, president of Agalloco & Associates, saw the usefulness of the guidance for validating pharma production processes and products. “The life-cycle model will result in development and validation exercises that provide relevant and meaningful information,” he wrote. “The link between the process parameters that influence the critical quality attributes will serve the industry well. The use of statistical methods will add a rigor to the validation efforts that has been sorely lacking” [1].

However, he expressed serious reservations (and shared them with FDA) about whether the PV guidance could easily be applied to processes and systems “less clearly related to end-product quality attributes.” This includes sterilization and aseptic processes.

“There are simply too many independent—and interrelated—variables in aseptic processing, and the most meaningful one of all lacks metrics of any type . . . Aseptic processing performed by human operators is devoid of any measurable variable that could be used to predict the outcome.” He concluded: “The statistical component of the guidance really doesn't work with respect to linking any process parameters directly to performance.”

Now that the guidance is official, we checked in with Agalloco to see if his views have softened. Far from it, it turns out. The guidance is a “terrible fit” for the validation of aseptic processes, he maintains.

“I've seen more confusion than clarity,” Agalloco says. “I've seen no indication in the final guidance or anywhere else that suggests things should be changed to accommodate sterility within the new guidance.”

Agalloco teaches regular courses on validation of aseptic processes, but has not changed them to reflect the new guidance. “There's nothing you can change in the practice of either sterilization or aseptic processing that is of any value to fit the guidance,” he says. “I see no need to adapt, because the adaptation will gain nothing of real value.”

The new guidance reinforces the need for science and process simulation testing—isn’t that a good thing? In general, yes, he says. But, “for aseptic processing its about set-up and interventions, and what the operator does in relation to them. Humans are awful subjects for DoE, QbD and all of the scientific buzz we hear about in relation to the guidance.”

Will the PV guidance dramatically change the way manufacturers approach the validation of sterilization processes—filtration sterilization, for example?

“Not in the least,” Agalloco says. “There's no suggestion that anything can or should be changed to match the guidance. Even FDA (Grace McNally, at PDA in San Antonio in April of this year) has stated that the ‘guidance doesn't specifically apply to sterilization.’ Making changes to fit these processes to the guidance is done at one's peril.”

The PV guidance recommends activities in three stages (process design, process qualification, and continued process verification), which depend on process characterization studies (with Key Process Input Variables, Design Space, etc.). Are most manufacturers able to adequately characterize their aseptic processes and sources of variability?

Says Agalloco: “Not at all. As the article [1] states, there's some possibility with sterilization as it relates to Stage 1, but that's about all that fits. Stage 2 & 3 lack adequate metrics to develop the confidence from what we can routinely measure in the process for sterilization so it's not a good fit there. Aseptic processing is just a horrible fit all around.”

 

We also consulted with Sartorius Stedim’s Maik Jornitz, current chair of the board at PDA, about whether the guidance will make a difference regarding the validation of filtration processes, one of his areas of expertise. “I do not think that the new Process Validation Guidance will change the process validation needs and activities surrounding sterilizing grade filtration,” he says. “The 2004 Aseptic Processing Guidance makes it very clear what is expected by regulators in regard to sterilizing grade filter validation, which is still very valid and unchanged by the new Process Validation Guidance.”

Will this guidance help filter end users to better understand which filter process input variables are "critical to quality"? “I do not know whether it will help, but it will raise the awareness and emphasis that there are critical variables within the filtration process,” Jornitz says. “The 2004 Aseptic Guideline touches upon and PDA Technical Report #26 describes in detail these critical process parameters, if the awareness is not already there.”

Jornitz, a frequent writer, speaker, and lecturer, has long preached a “science-based” approach to filter validation, and so believes the PV guidance will support this trend but is not necessarily a game-changer: “I believe everybody in the industry is working in accordance to a science-based approach,” he adds. “Therefore, guidances are only there to reiterate or support what should and is commonly done—or so I hope . . . I do not think that the Process Validation Guidance states something new here.” 

Green chemistry has ecological, financial benefits for Pfizer

When people hear the word "green" these days, they automatically think "environmentally friendly." But among chemists at Pfizer Inc. in Groton, the word also denotes efficiency, which equals a different type of "green" - money.

And Pfizer's local laboratories have been saving the company plenty of money - millions of dollars, most likely, though the company won't provide specific figures - over the past few years through a relatively new idea called green chemistry. Scientists in Groton are constantly reviewing and revising the chemical processes that go into the manufacture of top-selling medicines such as the cholesterol blockbuster Lipitor and pain reliever Lyrica, making sure new drugs are produced in the most efficient manner possible.

"Pfizer is a leader in both the research and implementation of green-chemistry and green-engineering practices," said S. Stewart Slater, a professor of chemical engineering at Rowan University in Glassboro, N.J.

By going green - which local scientists spearheaded at Pfizer a decade ago, though the chemistry principles date to the early 1990s - the making of pharmaceuticals is being done in a less wasteful, safer and more benign manner.

"By being green chemists, I think we provide a particular benefit to the environment," said John Wong, senior research fellow at Pfizer's Groton labs and leader of the eight-member Green Chemistry Team there. "When you use enzymes to do chemistry, they are not toxic and certainly environmentally friendly."

In the pharmaceutical industry, green chemistry often means the replacement of organic solvents with enzymes, commonly referred to as "nature's catalysts" and naturally occurring in all living organisms. Companies try to implement green chemistry ideas right from the start, because changing drug formulations after a product is out requires additional human testing for safety and effectiveness.

Eric Watters, environmental manager of the Groton facility and a team member, said the use of green-chemistry methods doesn't have a big impact on the local air and water because the pharmaceutical giant no longer has extensive manufacturing facilities here. It's at the company's drug-making plants worldwide that the use of green chemistry is most noticeable on the environment, he said.

The environmental impact is felt most profoundly with reductions in the amount of carbon dioxide released into the atmosphere. Efficiencies and cost savings come largely from reduced use of raw materials and significant cuts in energy use.

To give an example, Wong pointed to a new process for manufacturing Lyrica developed by his team in Groton that reduced carbon-dioxide emissions by 43 percent using one of Pfizer's measurement tools. The company expects a further reduction in emissions of 20 percent as it continues to refine the method through the end of next year, he said.

Avoiding chemical waste

"The pharmaceutical sector has embraced green chemistry most enthusiastically, perhaps because it has the most to gain," according to an article last month in Nature News. "Pharmaceutical plants typically generate 25 to 100 kilograms of waste per kilogram of product, a ratio known as the environmental factor, or 'E-factor.' So there is plenty of room to increase efficiency - and cut costs."

The company expects that green-chemistry processes used to reimagine the production of Lyrica will, over a 13-year period, avoid about 200,000 metric tons of organic chemical waste. Pfizer scientist Peter Dunn, who in 2006 became the pharmaceutical industry's first full-time green chemistry leader, has said the rejiggering of three product lines alone saved the company the cost of 500,000 metric tons of chemicals.

According to Pfizer spokeswoman Sperry Mylott, the company's drugs currently in late-stage development use 24 percent less solvent per kilogram than the most advanced compounds it was testing a few years ago, "thus achieving one of Groton's chemical R&D team's environmental goals two years ahead of schedule."

Chemists do small-scale experiments in Groton before trying out their ideas on a bigger stage with Pfizer's manufacturing partners, said local team leader Wong. The idea is to be as "atom economical" as possible, he added, meaning that less material used up front leads to less waste in the end.

"The company is quite good at implementing process improvements," he said.

Although the pharmaceutical industry in general did not embrace the principles of green chemistry right away - chemical companies faced with outcries after the Love Canal fiasco and the Bhopal disaster had a greater incentive - it now is more motivated, as drug discovery has waned and cost-cutting is getting more attention.

As far back as 1998, Pfizer scientists in Sandwich, England, had worked to improve efficiencies in the manufacture of Viagra, which at that point produced 105 kilograms of waste for every kilogram of product. Pfizer eventually reduced the E-factor to 8, meaning the production of Viagra became more than 90 percent more efficient.

"Ultimately, it's all economics that drives it," said Connecticut College chemistry chair Marc Zimmer. "You can't just let waste go down the drain anymore. You have to dispose of it, and that means you have to pay for it."

Improving production methods of antidepressant Zoloft as well as Viagra and Lyrica have won Pfizer major green chemistry awards. The 2002 Zoloft green chemistry project, conducted at the Groton labs, won the U.S. Environmental Protection Agency's Presidential Green Chemistry Award.

Early stage development

The local labs also have their own internal awards, and winners may designate the prize to an educational institution. In the past year, the prize went to Pfizer scientist Jamison Tuttle, who designated that the $5,000 award be given to his former Connecticut College professor Timo Ovaska, who in turn plans to use it for research stipends for summer students.

"Green chemistry is still in an early stage," Ovaska said, "but it's definitely having more and more of an impact."

Wong said Pfizer doesn't force green chemistry on anyone, but there is a constant effort to educate employees in the science. He added that chemists have been quick to embrace the concept and are always brainstorming and experimenting with new ideas for making pharmaceutical production less costly and easier on the environment.

"It's part of our day-to-day activities," he said.

Ordinary Measures : Everything I needed to know I learned in Freshman Chemistry 101

For Years, pharma has been the villain in most public opinion polls. But now, the tide seems to be turning. Last month brought buzz about the film, Extraordinary Measures. You’ve no doubt heard all about the inspiring story of John Crowley, a pharmaceutical exec who quit his job to fund research into cures for Pompe disease. Not only did he save the lives of his own, and many other, children, he opened up the field of orphan drugs.

Although critics are lukewarm, they say the movie does reveal to the public more of the complexity and challenge of drug development and manufacturing. What could be better than that? But lately I’ve been wondering about the “other” side of manufacturing—the side that could never make it to Hollywood: cGMPs and quality control. Drug recalls in the U.S. have been trending upwards. In the U.K., according to a recent study by Blueview Group, drug and medical device recalls increased 400% between 2004 and 2008, due mainly to manufacturing defects, packaging or labeling issues, or compromised sterility. 

Pharmaceutical quality control reached a climax in the news last summer, after FDA issued Genzyme a 483 for cGMP problems at its Allston Landing plant. This plant manufactures the orphan drugs Cerezyme and Fabrazyme, worth nearly $2 billion in sales each year. A dissident shareholder, Relational Investors, sued the company, its principal alleging that Genzyme overpaid for acquisitions and underinvested in manufacturing. The problems cost Genzyme dearly, as FDA did not approve its improved Pompe disease treatment (which is now being re-evaluated) and reportedly streamlined the approval process for a competitor’s product. Last month, Genzyme hired a new QC chief, and contracted with Hospira to handle filling. Relational withdrew its suit, and hopes to settle its diff erences with the company.

But the question still lingers. Is the industry, in its desperate attempt to acquire innovation and reinvent itself, underinvesting in core quality control operations? Last month saw another major pharma company, J&J, dogged by quality control issues. Th e company has led the industry in Lean Six Sigma and operational excellence initiatives, so this news may have surprised some. But J&J had to recall more lots of Tylenol and other over-thecounter medications, which were tainted with a chemical used to treat wooden pallets. FDA alleged that J&J was aware of the problem a full year before it took action.

It’s easy to point the finger at senior management. But is that the whole story? Is everyone on your team being rigorous about quality? We often lament about pharma’s silos and its “data rich, information poor” problem. But that doesn’t mean that each and every critical data point shouldn’t be recorded, transferred and shared. Last month, we interviewed experts on the topic of tech transfer, and found that people oft en fail to transfer basic information to internal partners, or external CMOs. Information is missing, isn’t recorded, and, in deals involving China and Japan, isn’t translated. And analytical methods and SOPs are the areas where people most often trip up. This has an obvious impact on CAPA and fundamental quality control.

Contributing editor and NIR expert Emil Ciurczak suggests that some have “gotten lazy and stupid” about documenting critical details. “Everything you need to know to pass an FDA inspection you learned in freshman chemistry class,” he says. One industry consultant recalls a consent decree in the 1980s, where a lab technician openly admitted to FDA to taking notes down in pencil, then changing them to ink later on. She also responded to questions about an SOP. “Nobody does it that way,” she said. “Everyone knows it won’t work that way.”

“How could anyone have hired such an incompetent tech?” you ask. But is it really that farfetched? Read any 483’s lately? It’s the ordinary measures, as well as the extraordinary ones, that count.

Biotech Production: Planning, Scheduling and Throughput Analysis with a Combined Theory of Constraints, Lean and Simulation Approach.

A major biotech company’s only final stage bio-manufacturing facility in the world was struggling to meet rapidly increasing customer demand. Unanticipated production delays and frequent starvations at critical parts of the operation were causing not only late and missed deliveries, but also the expiration of product batches at a cost of approximately $1 million per batch.

They had not been able to identify the root cause of their production delays, nor find a suitable solution. As a result, they were planning to invest $1.2 billion to add another 500,000 square feet to the existing biotechnology bulk manufacturing facility.  Before proceeding with a capital investment this large, it made sense for the team to make sure they had considered all other feasible solutions first and/or at the very least validated their assumptions leading them to the conclusion of needing additional space. They engaged ProModel Corporation to help. 

We recognized that this project would require a discrete-event simulation solution along with aspects of Lean and TOC (Theory of Constraints).  Lean is commonly applied in manufacturing in order to reduce and eliminate waste, TOC is used to help discover which issues are limiting the overall system performance and Simulation is used when the variability and interdependencies of a process or system are such that traditional problem solving approaches are too risky or inaccurate.

This article discusses how using a combined lean and simulation approach helped one pharmaceutical manufacturer produce two more lots per month resulting in additional revenue of $25 million/month as well as eliminating expired batches at a savings of $1 million/batch, without expanding the facility at a projected cost of $1.2 billion.

Due to a confidentiality agreement with the manufacturer we can not disclose their name, but we provide this case study and best practices article as awareness and exposure to the idea of using simulation in combination with Lean and TOC to solve complex manufacturing throughput and scheduling issues.

We worked together with the client’s project team using TOC, Lean and Simulation to do the following:

• TOC to discover the bottlenecks
• Lean principals as a way to develop the ideas and concepts that could help resolve the problems
• Simulation as a way to test and analyze these ideas and determine precisely how to implement the best ones, all without risking any interruption to the on-going production process. 
• An additional advantage of a simulation solution is that most of the time the organization also gains a problem solving tool and capability that can be used over and over again to solve and even prevent similar future problems.

ProModel’s approach is an iterative three phase process called VAO (Visualize, Analyze, Optimize). The remainder of this article will summarize how Lean and Simulation were used synergistically within this approach to achieve the client’s objectives. Within each of the VAO sections, there will be some best practices listed at the beginning, and then some specific examples of how those practices were used in this particular project.

The specific client objectives for this project were to:

• Uncover the root cause(s) of the unanticipated delays creating the late and missed deliveries.
• Develop a repeatable, accurate predictive tool that allows them to analyze and identify, in a risk free    environment, which potential changes will eliminate the current delays and help prevent future ones.
• Determine if, when, and how much additional capacity from a new facility would be required.

VISUALIZE Phase – Understand Your Current State Environment

Best Practices

The visualize phase helps the organization better understand their actual current operating state and sets up the entire project correctly in several ways:

• Ensures the right problem or issues are being solved. This is done by starting with the end in mind; identifying the actual results that need to be achieved, and then what type of output information the simulation model must produce in order to help make decisions on the appropriate process or policy changes.
• Helps the company truly understand how their current environment is actually operating through building, validating and verifying a current state model, not just how they think it’s operating.
• Often organizations gain a great deal of value from simply going through the process of gathering data and putting together VSM (Value Stream Maps) or Process Flow Charts without ever simulating.  If the maps exist, then the simulation step helps them to take advantage of work they have already done. 
• Building and validating the current state simulation model can then further enlighten an organization without even testing the first new idea by identifying through sensitivity analysis which processes or resources are really critical (bottlenecks) to meeting their performance goals so that you only spend time on improving the areas that really matter
• Builds trust in the simulation concept by allowing those involved to visualize the current operation and say “yes this is how things really do work around here”.This paves the way for the optimize phase so that when changes are proposed, there will be more confidence in accepting the results predicted by the model from implementing the changes.
• Provides a measurement of the gap between current and required performance

Project Implementation

In this case, starting with the end in mind, the project team determined that the model had to replicate not only the manufacturing process itself, but also the production planning/scheduling aspect of the current system as well. This necessitated taking into account parameters such as: workforce resources, process flow, inventory levels, availability and movement, equipment, scheduling, and product mix. The simulation output information generated had to enable the Production Planning Team to test schedules, visualize the impact on throughput and cycle time when changes are made to these parameters, and provide the optimum schedule to the Production Execution Team.

Therefore it was determined that value stream maps/process flow charts were needed for their manufacturing system including inventory policies and production planning/scheduling methods. Microsoft Visio was used to create the VSM’s and ProModel’s Process Simulator, a plug-in to Visio was used to convert VSM’s into simulation models. (below)

To develop this model it was necessary to collect current and historical data on the production operation and use that as a base line for setting up and validating the simulation model.

The VSM’s would serve as the virtual representation of the production process for the animated simulation runs. Customizable ProModel compatible Excel input templates were also designed within the tool to enable the team with the capability of changing model data for rapid “what-if” scenarios.  The model was then integrated with scheduling software. After running each scenario, the team was then provided with Gantt charts that allowed them to examine actual planned schedule performance.

Summary of Steps to Develop Model

• Microsoft Visio was used to map out the process flow and used as the virtual foundation for the model. If the analysts want to change or add a new process they simply change the flow chart and it automatically updates the model and the Microsoft Excel input templates.
• Excel input templates made it easy to change production tasks, process times, and the resource requirements.
• Scheduling software was integrated with the model and was used to evaluate the proposed schedules with Gantt chart output reports.
• Easy to use Design of Experiment capabilities in concert with a set of user definable Key Performance Indicators provided the method to rapidly evaluate system performance across an unlimited number of scenarios.

Working with the client project team it took about 8 weeks to create and validate an integrated production simulation and scheduling model.   After the model was built and historical data used to validate and verify that the existing model was with an acceptable range of accuracy of the real system, usually 95% or better, the next step was to begin analyzing the situation.

ANALYZE Phase – Identify Root Cause(s) and Brainstorm Potential Changes Using Lean Concepts

During the analyze phase the model is used to help identify root cause(s) of performance issues as well as to brainstorm ideas and create scenarios that might improve the processes to meet business objectives

Best Practices

Before beginning to test anything, utilize the current state model to view the animation and generate output reports that allow analysts to diagnose what issues are keeping them from operating up to the designed system performance levels. Lean concepts and thinking can then be used to develop a list of feasible ideas to test in order to improve performance based on truly knowing what is wrong.   It’s tempting to want to test everything because experimenting with the model can be “cool”.  However, from a time, cost and reality standpoint, you can’t test everything so it makes sense to test only what Management would actually consider implementing.

Once a feasible list of ideas was generated and prioritized typically the model needs to be enhanced to incorporate the actual changes to be tested.  Depending upon which changes are to be tested the model can be modified to include just the first test or all of the tests; this has to be determined on a case by case basis.

Lean methodology prescribes having a Kaizen Event in order to implement changes, where the changes are implemented based on value stream map analysis and the suggestions of the people doing the work at a particular station or process.  This is a good idea on much of the low hanging fruit.  However, when proposed changes are too risky or too complex to test with the traditional Lean Kaizen Event method, simulation is a more effective tool to conduct “Virtual” Kaizen Events.

Project Implementation

On this project, they used the validated model of their current state to observe the animated representation of the system as well as several types of output reports to help identify their underlying performance issues as follows:

1) The key bottlenecks or pacing processes changed radically depending on the product mix. If the product mix changed enough, an item that was on the critical path and crucial to delivery one month may not be on the critical path the next month. 

2) With a schedule and inventory based on the constant manufacturer driven PUSH system, the client couldn’t respond fast enough to the unstable changes in demand, which led to their debilitating system constraints.

The manufacturer’s Industrial Engineering (IE) team had previously looked at many aspects of their production system as possible causes for the inadequate throughput and subsequent batch expirations. However, until beginning this project with ProModel they had not seriously considered possible cause or solutions outside of the traditional plant floor improvements such as additional equipment or labor, or additional space as discussed earlier. This time around though, their IE team, working with us under the VAO approach, considered the entire production environment not just the plant floor manufacturing processes.

As a result, while collecting information and developing the current state model, the Industrial Engineering Team discovered that Production Planning was scheduling using a PUSH system. The team thought that changing to a PULL/JIT (Just-In-Time) system might help reduce the delays, which made sense considering the root cause discovered. This is very much a lean concept, because normally changing from a push to pull system helps to reduce waste such as excess inventory, prevent scrap, damage, and rework and obsolescence, such as the expiring batches that this manufacturer was experiencing. The team decided to pursue this alternative as the first option to test with the model.

Changing to a pull strategy required answers to the following questions before implementation:

• What levels of inventory should be used to ensure line continuance, but not result in lost batches due to expiration?
• If/when would additional labor be required?
• When in the future, if at all, would additional line capacity be required?
• More Info required here

Once the decision was made to analyze a Pull strategy, some additional functionality had to be added to the model including:

• User friendly input settings were implemented to adjust varying levels of inventory controls by sub-process and the different lot types which included vial, syringe, and drug type. 
• Provide Customized Input Templates to enable the team with the capability of changing model inputs for rapid “what-if” scenarios.
• Provide a Gantt Chart Report (figure 5.jpg) to enable team with the capability to examine actual planned schedule performance including the output of supporting services requirements
• Develop Scenario Runner interface for rapid “what-if” analysis of process improvement suggestions.
• Provide an iterative planning correction procedure to enable the team with the capability to examine the performance of the system and make iterative changes to improve and correct planning issues.

After updating the base model to be representative of a pull strategy, and verifying that it works correctly, the team moved on to the Optimize phase in which it would evaluate in detail if this new approach works, if so, what are the operating parameters, scheduling rules, inventory levels and policies that must be implemented in order to reach maximum capacity.

OPTIMIZE – Design the Future State Operating Environment

During the optimize phase, the model is utilized to test the ideas generated in the Analyze, in order to determine the optimum set of changes to make in order to reach the planned objectives.

Best Practices

When starting to use a simulation model to test ideas, scenarios are usually created and run in a particular sequence to help get at a result in the most efficient manner:

1) Run the “Current State” scenario in order to have baseline results available

2) Design and run scenarios from a high level, with only the level of detail/resolution needed down to lower level details.  Running scenarios with more resolution than needed makes finding the optimum solution more difficult than it needs to be.   

3) Test only the changes at the bottleneck or constraint to start with.  Until the bottleneck/constraint situation is resolved, testing other changes will not necessarily be meaningful.

4) Run additional scenarios with increasing breadth across the system and/or increasing levels of detail and resolution as needed until the optimum solution set is found.  This is the new future state environment.

5) Test the robustness of the system by varying input parameters to push the boundaries in order to see how much performance is affected when things don’t go according to plan. 

6) Finally, repeat steps 2-6 in an iterative fashion as required if the first strategy does not produce the desired improvement.

Project Implementation

Using the best practices steps above, the team utilized the model to run scenarios around schedules and inventory levels in order to predict and quantify the realistic throughput performance of their proposed PULL system.  Key Performance Indicators were available after each simulation run in the software output reports module.  These output deliverables included: Overall Cycle Time, System Throughput, Work-in-process levels and Resource Utilization. From each of these data charts the IE team was able to compare scenario results and refine each simulation run until the optimal integrated production schedule was discovered.

Some of the key items tested in modeling the pull system were as follows:

• Starting the precursor activities to the formulation and filling processes 5 days before the production date to allow for needed equipment or subassemblies to be manufactured.  
• The start date and time of the formulation and filling lots.
• The time lag between input start and formulation or filling lot start were controlled by delay tasks that appeared as inputs in the task controls tab of the input spreadsheet. 
• Both planned and unplanned downtimes affecting the schedule were modeled in a similar manner, using two pieces of information: the frequency and duration of each downtime.
• Inventory levels
• Product mix and batch/lot sizes

The solution confirmed their idea that the production environment had to be converted to a PULL system in order to meet the required customer demand and still have enough capacity to absorb predicted variation.  Additionally it took less than 8 weeks for the project team to arrive at this optimal solution and immediately they made the necessary changes to convert to a Lean, demand driven, PULL system.  

If optimize the model performance of the future state system with the PULL strategy would not have been sufficient, then the next iteration of Analyze and Optimize would have started, and a second idea or  strategy would have to be tested in addition to or in place of the PULL concept.

RESULTS

The simulation solution allowed them to define the right combination of scheduling sequence, product mix, batch size, in-process inventory and process changes that enabled them to meet customer demand virtually eliminated line starvations, batch expirations, and late/missed deliveries.

The client project team, working together with ProModel and the solution above, were able to accomplish the following:

• Determined how, the facility could produce two more lots per month, which has resulted in a monthly revenue increase of over $25 million.
• Defined the right combination of in-process inventory levels and process changes (going to a pull system) that would virtually eliminate batch expirations, which resulted in cost avoidance of over $3 million per year.
• Developed the capability to quickly schedule around the impact of significant unplanned downtimes.
• Provided the ability to optimize labor use and eliminated the need for additional staff.
• Provided a better way to do long-term expansion planning and predict when and where more line capacity would be required, thus eliminating the immediate need to spend $1.2 billion on additional manufacturing space.

DELIVERABLES

Deliverables to the customer for this project included the following:

• Recommendations arrived at with their IE and Production teams to convert to a pull system with precise metrics and specific process changes in order to improve performance to desired levels
• Repeatable strategic and tactical planning capability through the Customized Flexible, Reusable Predictive Modeling Application
• Technology Transfer Training and documentation to provide their team with a detailed understanding of the solution construction, input templates, Scenario Runner and output reports so they can continue using the model to plan and optimize the process into the future.

CONCLUSION

Best Practices

We have found the following four steps are used by our most successful clients in order to engrain simulation into the culture of the organization.

1) Build a model to answer the current questions with available data, don’t dive too deep right away.

2) Refine and expand the model as needed to answer tomorrow’s questions.

3) Build up internal core competency over time by developing two or three expert model builders and many experienced in using the models built for them. Organizations can build and benefit most of their own simple to medium complexity models this way

4) Use a simulation consultant for very complex situations.

Project Implementation

In this case simulation proved to be a powerful tool.  In general it can be used alone or along with other methodologies such as Lean and Theory of Constraints in order to help reduce the risk and improve the speed and accuracy with which an organization can do the following:

1) Perform root cause analysis on underperforming processes and systems.

2) Provide an objective sand box like environment in which to test new ideas, strategies, and policies in order to determine the most effective courses of action for each individual organization.

3) Gain an organizational capability for predictive, preventative performance planning and process improvement.

This particular Biotech Company now has a capability to constantly re-examine the performance of their system and make the changes needed to improve and correct planning issues before they occur and create significant problems.  By predictively analyzing their production planning, scheduling and throughput scenarios in a no risk simulated environment, they will continually make better decisions faster.