regrap november v3 - martine joosten...kepner and tregoe observed the practices of effective and...

In this issue:

• Rational decision making

• How much time is spent on Lifelong Learning programmes?

• Notifi ed Bodies in medical technology

www.topra.org

T O P R A – T H E O R G A N I S A T I O N F O R P R O F E S S I O N A L S I N R E G U L A T O R Y A F F A I R S

RegulatoryRapporteur

Vol 4, No. 11, November 2007

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TOPRA – The Organisation for Professionals in Regulatory Affairs

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Speakers

Monique Garrett (Octagon Research Solutions, Inc, Pennsylvania, USA) with contributions from Carlos Langezaal (Sanofi -Aventis, New Jersey, USA), Susanne Dorn (Amylin, California, USA), Paolo Biffi gnandi (VI.REL Pharma, Italy) and Christopher Bailey (TOPRA)

This second TOPRA North America Symposium, was well attended by approximately 40 delegates and speakers from the European Medicines Agency (EMEA), the United States of America Food and Drug Administration (FDA) and various pharmaceutical companies, CROs, etc. The topics for this symposium were Paediatric Regulations in the morning and Risk Management Plans in the afternoon, and the scientifi c portion of the day was closed out with a round table discussion with the presenters and industry representatives.

Opening remarks

Dr Carlos Langezaal, as TOPRA’s North America Head opened the 2007 North America Annual Symposium by welcoming the delegates and speakers. He introduced TOPRA as a global organisation for regulatory professionals and for those who have an interest in Regulatory Affairs in the healthcare sector. The current membership is drawn from over 50 countries. Effective regulatory professionals need to get the right information delivered at the right level at the right time, and that’s what TOPRA provides through its educational programme, including symposia like today. Subsequently, Carlos introduced TOPRA’s North America

Team members, Susanne Dorn, Gillian Ivers-Read, Aman Khera, Monique Garrett, Jacqui Dombroski, and Chris Griffett.

The meeting was co-chaired by Susanne Dorn, Amylin Pharmaceuticals and Dr Paolo Biffi gnandi, VI.REL Pharma S.r.l. Italy and member of the Board of Directors of TOPRA. The usual housekeeping rules were mentioned, and the morning session was started.

Paediatric Regulation: A perspective from the European Medicines Agency

Dr Natalie Seigneuret (EMEA)Dr Seigneuret spoke about Paediatric Regulations and supporting activities occurring at the EMEA. She noted that the objective of the regulation, which came into force on January 26, 2007, was focused on improving health of children by increasing the quality, ethical research into medicines for children and increasing the availability of authorised medicines for children, without delaying author isation for adults. Natalie described four key “pillars” of the regulation:

Paediatric Committee (PDCO) is to be established by July 26, 2007. This committee includes CHMP members, patient, family and healthcare professionals, experts from national competent authorities and EEA.

• Paediatric Investigation Plan (PIP) – An applicant must submit a request for PIP at end of Phase I unless duly justifi ed.This milestone requires early dialog and the need for procedures for modifi cations are foreseen as with amendments. The PIP must defi ne the overall strategy for paediatric development by the applicant.

The TOPRA 2nd North AmericaAnnual Symposium Meeting Report


AuthorMartine M.H. JoostenConsultant at Kepner-Tregoe LLC, The [email protected]

The nine steps of rational decision makingAdded value of a systematic approach to regulatory approval

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Key wordsDecision making, process management, regulatory affairs professional

Abstract

This article presents a methodology for an effi cient decision analysis process, which can serve as a framework for decision making. This may be particularly advantageous in complicated and multi-dimensional matters, with which the regulatory affairs professional is frequently confronted. The most important aspect of this analysis process is that the decision makers are forced to defi ne decision objectives fi rst rather than to start discussing different options. This enables an objective weighing of alternatives against relevant objective criteria. An additional advantage is that the decision analysis process is documented in clear matrices, on the basis of which a risk assessment is performed. The result is a transparent and effective decision making, which can easily be communicated to all parties involved.

The current challenges in decision making in a regulatory affairs environmentAn important aspect of a job as regulatory affairs (RA) professional within the pharmaceutical industry is providing input and advice concerning regulatory aspects of drug or medical device development. Although thorough regulatory advice may determine the success of a regulatory approval procedure, providing such advice can be a complicated matter in multidisciplinary situations. The reason for this is that there is often rivalry between different disciplines, each fi ghting for its own interests, led by their perception of the situation. The individual with the strongest infl uence is likely to dominate the discussion and force the decision. Others may accept those decisions

in order to save face and to avoid a confrontation. In such situations, the decision making is likely to be emotionally driven and focused on a discussion of preferred alternatives and irrelevant technical details. As a consequence, the end-goal may be completely lost from sight.

The benefi t of a structured decision analysis process has also been acknowledged by the European Medicines Agency (EMEA). Earlier this year, EMEA released a discussion paper on how to improve the transparency, consistency and communication of benefi t-risk assessments for medicinal products. It was recommended to use a structured approach, describing explicitly benefi ts and risks and describing uncertainties and their impacta.

Despite the importance of keeping the decision analysis process as transparent as possible, it is not common knowledge that relatively simple techniques are available to facilitate this. If RA professionals were more aware of the added value of a decision making process and of the systematic techniques that are available, they could more convincingly ensure that decisions were taken in the optimal way, also from the regulatory point of view.

The thinking pattern for making choicesParticularly in complicated, high risk, multidisciplinary situations as described above, people intuitively try to make decisions in a more rational way. This is done, for instance, by considering positive and negative aspects of certain options and evaluating those options against certain criteria. Evidently people look for tools and insights for making decisions. In the last decades, much research has been performed on this topic including that undertaken by Charles H. Kepner and Benjamin B. Tregoe. The roots of their research lie in sociology and anthropology. In carefully controlled experiments, Kepner and Tregoe observed the practices of effective and ineffective decision makers responding to complex, repetitive challenges. Their fi ndings were presented in The New Rational Manager and became the basis for the Kepner-Tregoe method for effective organisation management b. This decision analysis process, one of Kepner-Tregoe’s Rational Processes, is described in this article.

It is important to bear in mind that not every decision needs a formal decision analysis according to the process described here. The more complicated and multi-dimensional the decision, the more essential it is to go through the process systematically. Particularly in such complicated situations, a structured process provides transparency, which also benefi ts communication of the decision to different stakeholders, including senior management. An additional advantage of such a systematic approach is that the decision analysis process is documented in such a way that it is available for communication and archiving.

a Report of the CHMP working group on Benefi t-Risk assessment models and methods, EMEA Committee for Medicinal Products for Human Use, London, January 2007.http://www.emea.europa.eu/pdfs/human/brmethods/154047en.pdf

b The New Rational Manager, Charles H. Kepner and Benjamin B. Tregoe, Princeton Research Press, 1997.


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Regulatory Rapporteur – November Issue 2007

A nine step systematic approach: decision analysisThe key areas to cover in a decision analysis process are the following:

1. Clearly state the decision to be made (ie, the decision statement)

2. Set objectives

3. Classify objectives in must haves (“Musts”) and nice-to-haves (“Wants”)

4. Weigh the “Wants”

5. Generate alternatives

6. Screen alternatives through the “Musts”

7. Compare alternatives against the “Wants”

8. Identify adverse consequences

9. Make the best balanced choice.

Setting the purpose and objectivesThe decision analysis method starts with the decision statement, which provides the focus for all subsequent activities and discussions (step 1). Although this fi rst step may often seem superfl uous, it is a common pitfall to assume that everyone agrees on the purpose of the decision. In practice, each individual often has his own interpretation of what has to be decided upon. By creating a so-called decision statement, it is ensured that all parties agree on the purpose and end-result of the decision, thereby avoiding any misunderstanding in this respect.

Once the decision statement has been formulated, objectives are defi ned (step 2). These are defi ned as the criteria that will infl uence the choice, and which will assist to evaluate alternatives as objectively as possible. In order to prevent jumping to a preferred alternative, the development of objectives must be done prior to discussing any alternative. A common pitfall in decision making processes is evaluating advantages (pros) and disadvantages (cons) of certain alternatives, rather than to consider what characteristics the best alternative should have. In other words, which criteria should be used to evaluate an alternative?

Take this example of a biopharmaceutical company’s project team that had to take a decision on a complicated topic. The project had reached Phase 3 clinical development, and large clinical trials were being performed with a biotechnological compound, a complex glycoprotein. The clinical trial supplies for all studies were made with the compound produced at 500L scale. For several years, the manufacturing facility had been involved in the up-scaling of the production process for this compound. The main reason for the up-scaling was that the marketing department had forecasted to reach peak sales quickly after market launch. The expected high marketing demands had to be met. The intention of the team was to perform an extensive comparability exercise between the compounds produced at 500L and at 1800L scale during Phase 3. If the conclusion were that the up-scaled product was comparable with the 500L compound, the up-scaled production process would be included

in the registration dossier and claimed as the production process for delivering the market product.

At fi rst, the up-scaling activities looked very hopeful. The fi rst batches of drug substance produced at 1800L scale were released and extensively characterised. The conclusion was drawn that, from a physicochemical and biological perspective, the compounds produced at 500L and at 1800L scale were comparable. Since the project team intended to launch with the product produced at 1800L, they decided to proceed quickly with the validation of the up-scaled process. Then things started to go wrong. During the upstream processing of the fi rst validation batch, it appeared that cell growth was too slow and did not meet in-process criteria. The cause for this low cell growth was unknown. The cell growth of two subsequent batches of drug substance had the same problem, and it became clear that more research was needed to investigate the cause of the too slow cell growth. The unfortunate situation was that, to save resources, the project team had already decided to terminate the 500L scale production process some time ago. It was no longer in place. If it had to be reactivated, additional investments had to be made.

A decision had to be made on how to proceed – reactivating the 500L process or hoping for success with the 1800L process. The project team started to write a document in which the advantages (pros) and disadvantages (cons) of the different possible scenarios were listed. The result was a 15 page document, which was so complicated that some of the project team members even refused to read it. Instead of providing a clear and transparent overview, it did not directly and objectively compare the different scenarios. For example, how to compare the advantage of performing Phase 3 with a certain compound with the advantage of meeting market demands with an up-scaled process. The team endlessly discussed the different scenarios, actually comparing apples with pears.

In view of the importance of the decision, the project team decided to consult a professional with experience in decision making. The expert immediately started with giving the project team the assignment to fi rst formulating the so-called decision statement. They all agreed on the following decision statement “Choose the optimal way to produce drug substance (DS) for fi rst submission”. Amazingly enough, the market need, which had been driving the discussions, became not the intended goal; the real end-result to be achieved was the fi rst submission. Subsequently, the expert asked the team to establish objectives that must or may be met.

When developing objectives, the following should be considered: short- and long-term benefi ts/results to be achieved, resources to be used or saved (eg, budget limitations), restrictions applicable to the situation (eg, rules and regulations, production capacity), the absolute minimum that should be met (eg, test requirements). Objectives need to have a clear measure that indicates in what way an alternative meets the criteria (eg, maximise market supply needs as measured by x grams compound per year).

It is this step of defi ning objectives that is the heart of the systematic method as it forces a shift in the usual thinking pattern. Rather than to be tangled up in discussions about alternatives without having defi ned the criteria against which to measure these alternatives, one needs to step back and defi ne: “what is it that needs to be achieved?”

Not all objectives are equally important. Some are “must haves” (Musts) and others are “nice-to-haves” (Wants), and this needs to be classifi ed (step 3). Objectives classifi ed as “Must” are mandatory: they must be achieved to guarantee a successful decision. These are the minimum requirements that an alternative must provide to be taken into consideration. To determine whether an objective is a “Must”, the


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following 3 questions have to be addressed:

• Is this objective mandatory? eg, according to any rule, law, regulation, and guideline

• Is this objective measurable, with a set limit? eg, is there a minimum or a maximum?

• Is this attainable? Thus, can it reasonably be achieved?

If the answer to all three questions is “yes”, the objective is to be classifi ed as “Must”. If not, the objective is to be classifi ed as “Want”. “Must” objectives are the minimum requirements and not necessarily the most important.

To weigh the “Want” objectives (step 4), a relative value to each one of them is assigned. A scale from 1 to 10 can be used to show for each objective the impact it will have on the decision. The most important objective will be assigned the highest value (10), whereas all other objectives will be scored relatively to the most important one.

In the example of the pharmaceutical company’s project team, the team agreed on the objectives and its classifi cation. Some of them were easy as these were clearly documented, eg, budget constraints and GMP guidelines. Other objectives needed more discussion, as team members misinterpreted much of the phraseology used. The team was constantly challenged to make the objectives specifi c and measurable: what did they mean by “ensuring market needs”?

The discussions resulted in a decision analysis matrix (see Table 1) in which the defi ned objectives were classifi ed as either “Musts” or “Wants”.

Evaluating alternativesOnly after having completed all above-mentioned steps, alternatives are generated (step 5). The decision statement and objectives provide guidance in searching for alternatives. For the subsequent steps in the decision-making process, it is important to gather as much factual data as possible on the different alternatives. Factual data make discussions less emotional and more rational. A matrix can be developed to facilitate the search and recording of the data on the alternatives. A common pitfall is the lack of factual data to support the decision.

Each alternative is then compared against all “Must” objectives (step 6). An alternative that does not meet a “Must” objective, will be discarded from further evaluation. If after this evaluation process all alternatives have been eliminated, other options may be considered (ask experts, widen search) or the mandatory nature of all “Must” objectives may be reconsidered. After elimination of the alternatives that do not meet all of the “Must” objectives, the remaining alternatives will be evaluated against the “Want” objectives (step 7).

In the example, the project team identifi ed three possible alternatives: 1) going back to the 500L process and reactiving and validating it for market supplies, 2) try solving the issues with the cell growth at 1800L scale and validating the process for market supplies, and 3) validating the process at 500L and 1800L scale in parallel to increase the chance that at least one will succeed and be ready for registration and market supply. These three alternatives were compared against the defi ned “Musts” and “Wants” objectives (see Table 1). The optimal alternative appeared to be alternative 2, ie, the validation of the production process at 1800L scale.

What if…? Risk assessmentUp till now in the decision-making process, only the benefi ts have been taken into account. However, it is of crucial importance to also consider any adverse consequences and disadvantages that may be associated with the preferred alternative (step 8). This is done by identifying possible risks, the likelihood of their occurrence and their impact. The question is asked: “What risks may possibly be associated with the alternative that has obtained the highest score in the decision matrix?” By assessing risks at his stage, a fundamental, fact-based risk analysis can be performed. As the performance of each alternative has been documented in a matrix, the risks will be assessed objectively. After risk identifi cation, a plan can be defi ned to mitigate these risks.

It is common practice in decision-making processes to take the risks into account. However, the pitfall is to also include risks in the scoring of alternatives against objectives, which confounds the objective evaluation of the benefi ts of the alternatives.

Best balanced choiceThe last step is to make a decision (step 9). This is done by determining whether the possible risks associated with the optimal alternative are acceptable. If not, less optimal alternatives are to be considered. The identifi ed risks associated with a certain alternative may not necessarily be a limiting factor as long as the risks are either acceptable or can be appropriately controlled. If the risks associated with the alternative with the highest weighted score are unacceptable, the alternative ranked as second best becomes the optimal alternative. The best balanced choice is the alternative that meets all “Must” criteria, has the highest attainable score for the “Want” criteria and is not associated with unacceptable risks.

Guided by the expert in decision making, the pharmaceutical company’s project team proceeded with identifying possible risks associated with the alternative that was assessed as the optimal (ie, alternative 2). The Risk Analysis was documented in a matrix (Table 2). Several major risks were identifi ed which could potentially have a major impact on the ability to apply for a Marketing Authorisation. Particularly, failure to identify the cause of the slow cell growth and solving the problem in time, was considered to be an enormous risk. All were confi dent that all problems would eventually be solved, but the impact on timelines would be considerable and not acceptable. In view of the risks associated with alternative 2, the team agreed to move to the second best alternative, ie, alternative 1, thus to reactivate and validate the 500L scale process. The main risks associated with this alternative were identifi ed to be the high production costs and not being able to meet market demands after the fi rst year. These risks however were considered to be acceptable if regulatory approval would be obtained on time as planned. This was in line with the formulated decision statement, where fi rst submission had been defi ned as the end-goal. The project team decided to up-scale the production process at a later stage, after regulatory approval. Confi dent that the right decision was made, the project team presented the decision analysis to senior management and received approval. The fact that the team went through the thinking process of decision analysis meant the presentation of the recommendation was easier to do. The process gave structure and questions from management were easy to answer as the decision analysis matrix provided them with the basis for their proposal.


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Conclusion

Decision making in complicated multidisciplinary situations may be facilitated by using a systematic process such as the rational process as described by Kepner-Tregoe. The most important aspect of this process is that the decision makers are forced to defi ne decision objectives fi rst rather than to start discussing different alternatives. This enables an objective weighing of alternatives against relevant

objective criteria. An additional advantage is that the decision-making process is documented in clear matrices, thereby avoiding lengthy documents. The result is a transparent and effective decision analysis process, which can easily be communicated to all parties involved. By using this approach for complicated decisions with a high impact, the RA professional ensures that the best balanced choice is made in which the regulatory perspective is also taken into account.

Table 1. Example of a decision analysis matrix

Decision Statement: Choose the optimal way to produce drug substance (DS) for fi rst submission

Objective Weight Alternative 1: only validate 500 L processfor registration

Alternative 2: only validate 1800L process for registration

Alternative 3: validate both 500L and 1800L process in parallel for registration

Should not exceed the development budget of € 3.000.000

Must € 2.000.000GO

€ 1.500.000GO

€ 3.500.000NO GO

Quality, safety and effi cacy of product produced must be demonstrated

Must Yes, confi rmed in Phase 3 studiesGO

Yes, comparable from physicochemical and biological perspective.GO

Ensure availability of all documentation needed for submission on time (Q1 2008)

Must Yes, incl. suffi cient stability data in March 2008.GO

Yes, comparability exercise and suffi cient stability data available March 2008GO

Validated production process for drug substance according to GMP requirements (ICH GMP Chapter 7)

Must Yes acc. GMPGO

Yes, acc. GMPGO

Ensure market supply needs, ie, 300 gram compound per year

Want (9) Likely not enough(100 g/year).Score: 5 x 9 = 45

Meets market supply needs.Score: 10 x 9 = 90

Minimise costs (cost per batch)

Want (8) Cost of Goods € 200.000 per batchScore: 5 x 8 = 40

Cost of Goods € 100.000 per batchScore: 10 x 8 = 80

Total 85 170

Each objective is listed at the beginning of each row of a decision analysis matrix. Each objective receives a weight, which is then multiplied by the score of that objective in relation to each alternative. That produces a score for how well each alternative performs to the objectives. The scores are added vertically to produce the total score for each alternative. In this example, alternative 2 has the highest score; alternative 3 was eliminated from further evaluation because it didn’t meet the budget requirements.


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Focus

Are you in the food and feed additives industry and preparing for REACH ?

TOPRA is aware that regulations of the food

and feed additives industry are becoming more

complex. There has been interest expressed in

creating an email network for TOPRA members

working in regulatory affairs in the area, in order to

provide a forum for the discussion and exchange of

information and experiences in this changing field.

If you would be interested in becoming a member

of the network, send your details to:

Special Interest Groups

[email protected]

Regulatory Rapporteur – November Issue 2007

Table 2. Risk analysis of alternative 2

Risk Probability Adverse consequence Seriousness

If cell growth problems of 1800L scale process are not solved within two months

High Then, no validated production process available for submission on time

If major adaptations are needed to solve the cell growth issues at 1800L scale

Medium Then, the product characteristics may deviate from the one tested in the comparability exercise. A new comparability exercise must be performed

High

If the validation of the 1800L scale process is not fi nalised before regulatory dossier submission

Medium Then, issues with the validation may be identifi ed at a very late stage and may jeopardise regulatory approval and market launch

Medium

Before choosing the highest-scoring alternative, the project team considered the risks and adverse consequences, assessing the likelihood (probability) of each risk with a high, medium or low and verifying the impact if the risk is happening by attaching high, medium, or low seriousness to the adverse consequences. The result was to bypass alternative 2, due to the risks on the timelines and instead select alternative 1. The risks associated with this alternative (high production costs and low market supplies) were considered to be acceptable if regulatory approval would be obtained on time as planned.


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