forecasting

Measuring The Impact Of Health Social Networking

John Sawers — Thu, 01 Nov 2012 20:43:57 +0000

Précis:

Like most web companies, at HealthUnlocked we do our best to work out what factors make patients come back to our site or not.

But, because healthcare social networks like ours are still in their relative infancy, it is at times hard to know the real impact we have on patients’ lives - everything is evolving so fast. Of our 150 condition and wellness communities, only 40 have been around for more than a year. Yet these communities are now visited by over 300,000 patients each month so it’s really up to us to work out what effect we’re having. Is there any real value or is it just a talking shop?

The impact on the patient
We asked almost 600 users why they use HealthUnlocked and what, if anything, they gain out of it. It turns out that the single most important need we fulfil (95% of people we asked) is the most basic - to connect with others who understand their condition. Connecting allows them to ask questions, share experiences, provide help, and receive support. Obvious, you might say, but you never know until you ask.

There are other things we learned:

75% of members report feeling less isolated
60% of users report significantly better understanding about treatment options
94% of users say HealthUnlocked has been useful or life-changing

The impact on the patient-physician relationship
Our hypothesis is that better informed, better supported patients lead to more productive and efficient patient-physician interactions.

But what do our patient users say?

55% feel better informed when they speak to their healthcare team
60% feel that they have a greater understanding of how to manage their condition

The impact on how the patient voice is heard beyond the clinic
Our semantic engine tags and structures all the patient reports and discussions taking place in the platform. This is done by mapping and aligning language used by patients to talk about their health with established medical terminologies. It allows analysis and filtering of content based on drugs/treatments, conditions, symptoms, issues/concerns and much more. By working with a network like HealthUnlocked, researchers can hear and receive patient insights in real time, outside of the artificial constructs of traditional surveys and focus groups. The impact of the ‘real-world’ patient voice on research and strategic decisions is something you can almost visibly see emerging in industry month to month.

It will change the way companies learn about the impact of disease, how patients experience their drugs and allow them to deliver a more responsive and granular service.

Beyond the forum
Services like HealthUnlocked are becoming an integral part of many patients’ health journeys and an invaluable resource in many doctors’ professional days. Today, health social networking resides at the fringes of medical practice, but it is becoming part of routine patient practice and increasingly something that can’t be ignored.

http://www.healthunlocked.com/

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Patients Centricity Canada

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Pharma forecasting: The changing role of patients

Andrew Tolve — Thu, 02 Feb 2012 12:44:30 +0000

Précis:

Milos Graonic, senior vice president, global leader of Nielsen BASES Pharmaceutical Practice, on how to mine patient data for forecasting insights

The intersection of the Internet, social media, and mobile has created a new dynamic in healthcare. Today’s patients have more access to information and to each other and can thus exert more influence on their treatments and the healthcare system at large.

And yet, some pharma companies continue to operate as if this shift were merely theoretical, without tangible impacts on their brands or their bottom lines. As a result, forecasters are often asked to use the same old models to predict what Milos Graonic, senior vice president, global leader of Nielsen BASES Pharmaceutical Practice, describes as a fundamentally altered landscape.

“In the past, the patient was only used in that first step of a [forecasting] framework, pretty much as an object,” Graonic told eyeforpharma’s recent Pharma Forecasting Excellence conference in Berlin. Moving forward, it will be critical to determine “who the patient is and what can happen to that patient” in order to create accurate forecasts.

He estimates that of 20 forecasting requests that come across his company’s desk, all 20 have a physician arm of research. Only four of them request patient research. “We are completely underestimating what’s going on,” Graonic said. There’s “a perfect storm” gathering on the horizon, unless forecasters devise a framework to incorporate patient influence into new product forecasts.

Integrated models

Traditional forecasting models rely heavily on physicians. Forecasters examine the epidemiology of the disease, the size of the market, the competition, the price of reimbursements and other constraints and weigh these against physician demand.

But what happens in a world where patients begin to engage doctors, question them, and ultimately exert influence over the medicine or treatments they prescribe? New statistics from Nielson suggest that 15 percent of patient visits include a request for a specific drug. Forty-one percent of those requests are granted.

Finally, the research suggests that 30 percent of overall prescriptions written are heavily influenced by patients. “Physician demand no longer equals market demand,” Graonic said. The need for a model that weighs physician demand against patient needs is therefore paramount.

Understanding patient needs and their influence on demand requires forecasters to look beyond standard patient flow and anonymous patient level data. Thankfully, finding and listening to the patient voice has never been easier.

Mining patient conversations on social media sites and patient forums can reveal what patients respond positively and negatively to with certain products on the market, and how their alignment differs from that of physicians. Forecasters can also mine patient searches on search engines like Google to gather insights into what types of information patients are pursuing.

When forecasting flu medicines, for instance, it can be difficult to find concrete data about where to focus a forecast. Companies like Google track flu trends by monitoring and aggregating when searchers click on information about the “flu.” That trend data turns out to be an excellent predictor for where the flu will migrate, “because if your neighbor or your wife or your kids start sneezing and coughing you’re quickly [online searching],” Graonic said.

“It’s one of the best predictors,” and it’s a valuable technique that can be replicated for other product forecasts.

Proprietary patient data

Forecasters can also conduct primary research to better understand what will drive patients toward a medicine and how that will influence price, reimbursement, and sales. Graonic gave an example of a forecast he conducted where his team interviewed physicians around the world, presented them with specific patient cases, and asked them the likely outcomes.

One product they predicted would receive 33 percent adoption from patients. Similar interviews conducted with patients around the world determined that, in actuality, that same product is hardly ever used. “The physician-only model was dramatically off,” Graonic said.

Graonic recommends patient surveys and interviews as a valuable way to secure proprietary patient data. He also recommends simulating patient-physician dialogue.

Nielsen uses a process called ‘e-talk’ whereby the company interviews physicians, presenting a series of scenarios with patients and asking how these various scenarios would influence their prescribing behavior. Then they conduct the same process with patients, measuring when patients pose the questions they’re most interested in and to which physician answers they respond enthusiastically.

“We [need] to figure out how these other pieces that people are discussing out there on social networks, how much they can influence patients and a physician and where the dialogue can take our client in the future,” said Graonic.

For all the latest on forecasting, join the sector’s other key players at Forecasting Excellence Europe on June 14-15 in London and Forecasting USA in October in Boston.

For an overview of eyeforpharma’s forecasting coverage, see Highlights from eyeforpharma’s Forecasting coverage.

For more on patients, see Special report: Patient's Week 2011.

For exclusive business insights, download eyeforpharma’s Pharma Emerging Markets Report 2011-12, Pharma e-Marketing Strategy and Pharma Key Account Management Report 2011-12.

For all the latest business analysis and insight for the pharma industry, sign up to eyeforpharma’s newsletters and follow us on Twitter.

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Pharma forecasting: How to fine tune market research

Andrew Tolve — Thu, 19 Jan 2012 13:37:33 +0000

Précis:

Todd Johnson of Kantar Health outlines how market research can be honed into reliable data to improve forecasts

There’s a curious fact about primary market research: Typically, it’s wrong.

It does, of course, provide some bearing on how physicians perceive your product and plan to prescribe it once it’s launched. But as a measure of future market share, time and again primary market research paints an inaccurate picture. Indeed, the discrepancy between preference share (the market share that primary market research estimates) and actual market share is often 50 percent or higher.

There are a number of reasons for this discrepancy, according to Todd Johnson, senior director of forecasting at Kantar Health. For one, during primary market research, physicians are forecasting their future plans based on bullet points in a survey. “It’s very difficult to meet the reality of what’s going to happen two or three years down the line, or maybe even a year from now,” Johnson said at eyeforpharma’s Pharma Forecasting Excellence conference in Berlin.

Secondly, primary market research generally assumes equal access, whereas in the real world different tiers, agencies, and organizations can restrict access, and affordability weighs more heavily on prescribing behavior.

Furthermore, primary market research overlooks feedback mechanisms; if physicians start to prescribe a drug and receive negative feedback, that will impact their future prescribing. It also ignores counter detailing; once a product launches, sales reps from pharma competitors will present arguments on behalf of existing drugs. “As good as market research is, no matter how large your sample size or how rigorous your approach, it’s still a contrived exercise,” said Johnson. “It’s not reality.”

Subjective adjustments

Johnson stops short of arguing that companies should cease primary market research altogether. As he points out, market share could theoretically be anywhere from zero to 100 percent. That’s a wide range, and primary market research helps narrow the gap.

Still, forecasters must take additional steps to hone this research into reliable data entries for their forecasts. “If we are going to spend the time and effort on the market research, we should spend an equal amount of time and effort on making the adjustments,” Johnson said.

The standard approach to adjust primary market research is to use a rule of thumb, wherein forecasters dock a standard amount like 33.3 or 50 percent from preference share so that it more closely resembles market share. Johnson argues against this approach because forecasters who use a rule of thumb almost always end up changing it based on a given situation. “They’ll look at it and say, ‘That’s too much or too little,’ which then makes it just as subjective as if they hadn’t had a standard rule of thumb to begin with,” Johnson said. And this subjectivity can have big implications for forecasted revenue.

Let’s say a preference share of 20 percent yields estimated revenue of $600 million. If a company’s rule of thumb is to decrease that preference share by 33.3 percent, that means market share will yield revenue of $400 million. If a forecaster decides to increase that rule of thumb to 50 percent based on the specific situation, revenue drops to $300 million. That’s a $100 million difference in projected revenue based upon a subjective adjustment.

“I would argue that unless you have some really sound support behind a rule of thumb [like a normative database that provides historical trends], it may not be a good idea to always apply a set percentage,” Johnson said.

If companies insist on sticking to a rule of thumb, Johnson recommends that they at least standardize the way they adjust it, with middle range preference shares regularly getting higher adjustment rates than high or low preference shares. “Physicians are good at picking out the stars,” Johnson said. “If it’s a good product, they will use a lot of it. On the other hand, if it’s a dog, a dog is a dog and they will probably not use a whole lot of it.”

In the middle ground, however, they have a more difficult time making decisions due to the parity among drugs, and follow-through rates will be consistently lower than anticipated.

Verbal probability scales

A good alternative to a rule of thumb is a scale that correlates verbal assertions to internal commitments, like the Juster scale. In the wake of World War II, the US Federal Reserve began polling the public’s intent and likeliness to buy durable goods like TVs and cars. The results were used to predict what the financial status of the US economy would be in the coming years.

Gradually, a correlation began to emerge between verbal commitments and an individual’s internal commitment to follow through on that intent. In 1966, an academic named F. Thomas Juster conducted further research on the subject and developed a comprehensive scale to adjust for the disparity between words and actions, intent and follow-through.

The Juster Scale is an 11-point scale with specific follow-through percentages linked to each point. For instance, individuals who give a score of eight or more have a better than 50 percent chance of following through on their intent. “This makes a lot of sense because my ‘very probable’ may be very different than your ‘very probable’,” said Johnson. “But if we assign a number to it, we can relate those things, so people have a better chance of being accurate with their responses.”

Granted, durable goods like cars and TVs are a far cry from drugs, but Johnson argues that forecasters can use the essence of the scale to create tailored algorithms that serve as standardized proxies for prescribing. Due to the elasticity of these algorithms, the adjustment for different preference shares changes in a standardized way, but not in a linear standardized way as a rule of thumb does. “When we use something like the Juster scale, we weed out those physicians who are not going to prescribe at all by using these probabilities” to arrive at market share, Johnson said. “We not only look at the depth of interest but the breadth of interest.”

Awareness, trial and repeat purchase models

Another scale that forecasters can use as a template for preference share adjustment is the Fourt-Woodlock equation. This scale emerged from research on consumer packaged goods. It estimates the total volume of purchases per year based on individuals who make trial purchases and repeat purchases of a product within the first year.

Consumer packaged goods are closer proxies for the pharmaceutical industry because consumers buy goods like cereals and pastas more regularly than they buy cars or TVs, just as physicians interact with prescriptions on a regular basis. The difference is that consumer packaged goods incorporate more TV and print advertising, sampling, and couponing, whereas pharma marketing primarily involves sales rep detailing.

Therefore, Johnson says, forecasters still need to create a pharma-specific model from the standard equation that predicts physician awareness. They also need to take into account which country they’re measuring, because the impact of promotion is higher in some countries than in others. “This isn’t the whole adjustment, but it gives you a good read on what a company’s efforts will do to impact follow-through,” Johnson said. “If you can adjust your promotion depending on how many sales details, how much journal advertising, that’s going to affect the awareness and potentially the follow through from the physicians.”

If forecasters want to account for the overstatement inherent in primary market research and run different scenarios based on their promotional assumptions, this is the ideal way to calculate it, according to Johnson.

For all the latest on forecasting, join the sector’s other key players at Forecasting Excellence Europe on June 14-15 in London and Forecasting USA in October in Boston.

For an overview of eyeforpharma’s forecasting coverage, see Highlights from eyeforpharma’s Forecasting coverage.

For exclusive business insights, download eyeforpharma’s Pharma Emerging Markets Report 2011-12, Pharma e-Marketing Strategy and Pharma Key Account Management Report 2011-12.

For all the latest business analysis and insight for the pharma industry, sign up to eyeforpharma’s newsletters and follow us on Twitter.

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Forecasting 2.0: How to make forecasting a strategic imperative

Andrew Tolve — Sun, 06 Nov 2011 17:52:00 +0000

Précis:

Prasad Saraph, business partner at Bayer HealthCare, explains why forecasting must reflect an organization’s collective intelligence

Though the worst of the financial crisis may have passed, pharma companies still face high capital costs across the industry, which has intensified the need to trim the fat from working capital.

Forecasting is a key lever to manage this challenge. Forecasting can illuminate where inventories can be reduced and how to free up idle capital locked internally.

It can also clarify how to use this capital judiciously—at the right place at the right time in the right amount.

Moreover, as companies seek to negotiate the volatility of emerging markets, the uncertainties of healthcare reforms, and the changing demands of customers, forecasting should come to the fore as a way to optimize the changing pharma landscape.

“Forecasting the existing portfolio as well as future revenue streams is critical for our industry in the 21st century,” Prasad Saraph, business partner at Bayer HealthCare, told the audience at eyeforpharma’s Pharma Forecasting Excellence Europe conference earlier this year.

“The companies [that] are good at these things will emerge as leaders over the next five to 10 years. The others will struggle.”

Addressing forecasting flaws

To claim this competitive edge, companies need to evolve their forecasting practices.

Responsibility for forecasting today often is divided among various departments—financial, logistical, sales, marketing, a long list.

The result is that forecasts sit in various silos.

“People don’t like to correlate the different types of forecasts together,” Saraph said. “They like to keep them separate.”

This can lead to a lack of integration and gaps in knowledge from one department to the next; contradictory objectives often ensue.

A second problem that can plague forecasting is lack of senior level buy-in.

Oftentimes, Saraph said, “forecasting is treated as a necessary evil rather than as a strategic toolset.”

Even if senior managers convey support to forecasters, they often turn around and push revenue numbers that are contrary to the forecast.

“There’s a huge gap between intent and message,” Saraph said.

When the financial crisis hit, Bayer asked Saraph to overhaul the company’s approach to forecasting.

Two years later, with a new model in place, the company has achieved its targets in terms of inventory reductions and forecasting accuracy improvements.

Forecasting 2.0

The forecasting model that Bayer envisioned and executed is built around the idea that forecasting is a strategic imperative.

Forecasting can no longer be passed off on various departments without alignment.

Rather, the new goal is consensus forecasts that represent the collective intelligence of the organization.

In specific countries, finance and logistics managers work in tandem with marketers to provide numbers and share information.

“It is important to have consensus owned by all of the organization in a country for all brands, and that drives one number forward,” said Saraph.

Regarding financial and logistical forecasts, the numbers don’t have to be the same, but organizations need to be aware of the differences, not ignorant to them.

Second, Bayer made forecast quality performance globally relevant.

Third, Bayer ensured that head forecasters are given adequate organizational power and training so that they can challenge other parties and get a consensus on the right number.

The company also prioritized using forecasting tools for straightforward forecasting functions so that human resources could concentrate on non-standard business forecasting.

“We all have these nice forecasting tools,” Saraph said. “Rely on these systems to do most of your normal business and focus your resources on the difficult tasks.”

Finally, Bayer has encouraged active involvement of key customers in the forecasting process and in demand shaping.

Demand shaping does not entail manipulating the demand, Saraph said, rather “educating key customers, wholesalers, and distributors about how to sense demand in markets and then accordingly how to respond.”

A new kind of forecaster

With this new approach to forecasting comes the need for a new type of forecaster.

“It’s the difference between a calculator and an iPad,” Saraph said. “It’s a significantly different role.”

Forecasters have traditionally been veterans of logistics or controlling with little specific training for the forecasting function.

The new forecaster needs to be a business manager with exposure to different facets of running the business, like marketing, sales, strategic planning, supply chain, manufacturing, and regulatory.

“We do expect the person to know what happens in these different and disparate functions,” Saraph said.

“Only then can you be a good forecaster and challenge these opinions from different functions.”

Forecasters don’t need to be whiz kids when it comes to IT, but they do need to be trained in the fundamentals of forecasting—what errors and time spans to use, what trends to rely on, where to find outliers, what ranges to set, etc.

Furthermore, they need to have experience managing peers and interacting with senior-level leaders outside of their direct reporting lines. This enables them to challenge weak forecasting views, to steer managers toward proper numbers, and to keep the department focused on solutions rather than distractions.

“All of us deal with noise in the planning world,” said Saraph.

“This noise comes day in and day out. There is a stock out, the plane landed late, a customer has held up the shipment, and so on.”

Most of this noise is due to short-term, operational hurdles that don’t signify larger problems.

“We should be able to phase them out and only focus on issues that are sustainable and have potential to create long-term problems,” Saraph said.

Finally, forecasters in the 2.0 era must be able to present forecasting updates and conclusions to senior management succinctly and in a manner that elucidates where support is needed and where opportunities lie.

“The last thing that any senior manger wants to see is a detailed Excel chart with SKU numbers and the data for the last 12 months and the next 12 months,” said Saraph. “It’s very easy to get lost in the details.”

Instead, forecasters should highlight those issues where specific decisions must be made.

If an organization is projecting product launch volume and the forecasting and marketing teams have come up with significantly different numbers, you need senior management to make a specific decision about that discrepancy.

“We should be able to present a succinct summary to this person and to highlight those issues where the decision is needed.” (For more on presenting a forecast, see When forecasters take the floor: 6 tips on presenting a forecast.)

That’s the ultimate goal of forecasting in the changed pharma landscape, said Saraph—to highlight critical issues and facilitate specific decisions that strengthen a company. (For more from Prasad Saraph, see Forecasting Europe: The key to competitiveness.)

For more on forecasting, join the sector's other key players at Forecasting Excellence Europe on June 14-15 in London and Forecasting USA in Boston in October.

For an overview of eyeforpharma’s forecasting coverage, see ‘Highlights from eyeforpharma’s Forecasting coverage’.

For exclusive business insights, download eyeforpharma's Pharma Emerging Markets Report 2011-12 and Pharma Key Account Management Report 2011-12.

For all the latest business analysis and insight for the pharma industry, sign up to eyeforpharma’s newsletters and follow us on Twitter.

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Will biobetters beat biologics?

Angelo DePalma — Fri, 14 Oct 2011 20:32:55 +0000

Précis:

Angelo DePalma explores how many pharma firms are focusing on improved molecules, or biobetters, to optimize existing portfolios and increase market share

The term ‘biobetter was coined by G.V. Prasad, CEO of Dr. Reddy’s Laboratories, at a bio-investor’s conference in Mumbai in 2007.

Today, perhaps, Prasad is the only person on earth who knows what the term means.

Biobetters, also known as biosuperiors, are one of the three general types of follow-on biologic.

Where biosimilars are ‘generic’ versions that seek sameness and innovator drugs incorporate altered drug function while retaining familiar (but purposely not identical) chemical structure, biobetters fall somewhere in between. (For more on biosimilars, see ‘Forecasting the potential of the biosimilars market’ and ‘Forecasting the future of biosimilars’.)

Given today’s economic climate and regulatory aversion to risk, larger pharmaceutical and biotechnology firms are the most likely to succeed in biobetters.

Pfizer’s acquisition of Wyeth in 2009 was in good part due to a desire to compete in biobetters.

Its projects include two for improving Biogen Idec’s Rituxan lymphoma drug and another to increase the half-life of Enbrel, for treating rheumatoid arthritis.

Similarly, AstraZeneca’s $15 billion purchase of Medimmune was meant to sidestep biosimilars and focus on biobetters.

Other large-cap players include Merck, Lilly, Amgen, GlaxoSmithKline, and Aventis.

But with enabling technologies as diverse as they are, smaller players are also getting into the act, for example, Xencor, Itero Biopharmaceuticals, Femta, PolyTherics, Nexar, and iBIO.

Biobetters are regulated as innovative drugs, typically requiring a full-blown Biologics Licence Application (BLA) in the United States.

Biosimilars, by contrast, may be approved through an abbreviated regulatory pathway and marketed based on its similarities to the original molecule.

In practice, regulators will probably treat all three follow-on types as innovative medicines, at least early on.

Marketing and sales efforts will be highest for innovator and biobetter drugs, but still substantial for biosimilars.

Regardless of the approval path, time-to-market benefits and cost savings typical of generics are inaccessible for biobetters.

Development strategies

Biobetter development strategies fall into three basic categories: changes in chemistry, alterations in formulation, and innovative delivery.

Within these treatments lie numerous individual tactical plays, such as modifying the FC region of an antibody to slow degradation and improve half-life, altering glycosylation to improve immunogenicity or duration of effect, attaching stabilizing structures like polyethylene glycol, needle-free injection, and pill-for-injectible switches.

“The possibilities are limited only by the creativity of marketing people,” says Ronny Gal, senior analyst at Bernstein Global Wealth Management in New York.

Changing the delivery route is arguably the most straightforward regulatory pathway for biobetters.

Switches to pills or patches from injectible dosage forms, or to needle-free injections, are tried-and-true techniques.

But abbreviated approval trajectories can never be assumed for biologicals.

“It’s not as simple as, ‘Here’s an approved device. Here’s an approved drug. Put them together and go,’” observes Paul Wotton, president and CEO of Antares Pharma.

Antares supplies TJet®, a needle-free injector, for Teva Pharmaceuticals’ pediatric human growth hormone product.

Pfizer, Genentech, Serono, Lilly, and several smaller players, who divide $1.3 billion in sales per year, dominate this crowded market.

Teva’s original needle-based product had barely penetrated the US market after three years, with just 2% of sales.

Since adopting the Antares delivery system 18 months ago, market penetration has doubled.

In 2009, Antares interviewed executives at 25 pharmaceutical and biotechnology companies, including blue chips, generics manufacturers, and development-stage firms.

According to Wotton, all anticipated that devices would become increasingly important in the creation of biological therapeutics.

If these data hold, then biobetters should be a boon to formulation and delivery companies.

Yet a good deal of this exciting technology remains unexploited.

“We were developing injection technology for peptides and proteins 20 years ago, but it has taken all this time for the pharmaceutical product market to catch up,” says Wotton.

A related biobetter strategy, combining drugs, is a favorite of John Plachetka, CEO of Pozen, who notes, “Almost all drugs are non-optimized.”

He cites a recent editorial by Dr. Janet Woodcock, who heads the FDA’s Center for Drug Evaluation and Research, in the New England Journal of Medicine.

Woodcock observed that the greatest advances in infectious diseases and cancer therapies resulted from the combination of two or more agents administered simultaneously.

Her agency has issued draft documents urging drug developers to consider this approach.

This same strategy, which has made AIDS a manageable disease, says Plachetka, is under-exploited with biologicals, with the exception of anti-cancer monoclonal antibodies (Mabs), which are frequently administered with standard chemotherapy agents.

“The time has come to abandon the silver-bullet theory for a more practical approach that recognizes the multi-factorial nature of disease,” he says.

Biobetters versus innovative biologicals

A good deal of fuzziness exists in the realm separating “optimization” (biobetters) from chemical synthesis (innovative biologicals).

Few could argue that altering a protein’s chemical backbone, even by one or two amino acids, does not create a new molecule, yet these fall under the biobetter category.

Maxygen employs a molecular technique, MolecularBreeding™, to shuffle a protein’s building blocks and combines these with add-on strategies like PEGylation.

Its clinical-stage portfolio includes a white blood cell-boosting improvement on Neulasta, which is currently in phase II, an improvement on a Novo Nordisk clotting factor in late phase I and a mutated version of Bristol-Myers Squbb’s Orencia arthritis drug in early preclinical evaluation.

Markets for the three originator molecules total $4 billion per year.

Maxygen’s mantra, enunciated at a recent Goldman Sachs conference, is “any protein can be optimized.”

Similarly, antibody fragments are at the cutting edge of biobetters.

These molecules, which consist of the active regions on antibody drugs, are much smaller and easier to manufacture than Mabs.

Numerous US firms are working on these. Among them is Nektar Therapeutics, which made its name with PEGylation (through Neulasta) and now applies similar strategies to antibody fragments to create what might be termed “double-bio-betters-betters.”

Chemical changes need not be as drastic as altering the amino acid sequence.

Switching expression systems is enough to affect glycosylation patterns, which may affect safety and efficacy, although the magnitude of this effect is debated.

One thing is certain: Chemical changes, however subtle, will alert regulators to potential safety issues.

Higher risk, higher reward

The emergence of biobetters has taken some of the luster off biosimilars.

For example, Israeli generics firm Teva, known for its small-molecule knockoffs, has been selling its version of Amgen’s Neupogen (filgrastim) white blood cell booster in Europe since 2008.

The eponymously named product, TevaGrastim, was approved under abbreviated regulatory designations in several European countries.

US approval, which has been delayed by regulators for 18 months, is expected under a full-blown BLA, meaning TEVA had to conduct all three phases of human testing.

Although Amgen has fiercely opposed the US debut of Teva’s biosimilar, the company’s downside is limited in that Amgen has already moved on to a biobetter version of the drug.

Neupogen’s annual US sales are around $900 million, while revenue from biobetter Neulasta (pegfilgrastim), a PEGylated version of the protein, exceed $2.5 billion.

Bassil Dahiyat, CEO of Xencor, believes that the business case for biosimilars is rather bleak in developed nations, and that biobetters represent a much more exciting opportunity.

Dahiyat describes biogenerics as a “low risk, low reward strategy” while biosuperiors are “higher risk, higher reward.”

He reasons that while clinical risk for biosimilars is lower than for biosuperiors and new biological entities, it is not zero.

Add to that uncertainties around human testing, reimbursement and competition, the burden of demonstrating similarity (but not superiority), and the almost assured need to employ BLA-like sales and marketing, and biosimilars—particularly complex molecules like Mabs—lose much of their attractiveness.

“The clinical path will be somewhat shorter, but if any safety signals arise you’re toast,” says Dahiyat.

He cites the case of Medimmune’s Synagis antibody for preventing respiratory syncytial virus in children.

The company sought approval of a second-generation biobetter through a full Biologics License Application, but the FDA rejected the drug based on a non-significant rise in mild infusion reactions.

The lesson is clear for manufacturers of any follow-on biologic: Safety signals will not be tolerated.

Competing on value

By Dahiyat’s thinking biosimilars should thrive in price-conscious “pharmerging” nations where consumers pay for their own medicines, and to a lesser degree in single-payer wealthy nations, but not Stateside. (For more on emerging markets, see‘Getting into the Indian pharma market’, ‘The Middle East: A pharma market in the making’, ‘Reassessing Russia's pharma market’; ‘Breaking into the Brazilian pharma market’; ‘Cracking the Chinese pharma market’; and‘How to get ahead in 'pharmerging' markets’.)

Yet conventional wisdom holds that in the US high entry costs and lack of competitive vigor will lead to modest price erosion—perhaps 15 to 20 percent—for biosimilars compared with the innovator molecule.

Thus, biosimilars and biobetters will be compete based on value, with the former being cheaper and the latter more effective.

Bernstein Global Wealth Management’s Gal counters that biosimilars, and perhaps the entire panoply of follow-on designations, could experience price drops similar to those of generic small molecule drugs.

High gross margins for biologics, he argues, will assure competition and price erosion: “You can drop the price from $10,000 per patient per month to $1,000 and still make an eighty percent gross margin.”

As with biosimilars, biobetter developers have tested the regulatory waters with relatively low-risk molecules like cytokines and hormones, which have long and admirable safety records.

“The tumor necrosis factor market is one big ‘biobetter,’” Gal notes. These include the antibody TNF blockers Enbrel, Humira, and Remecaid.

Within this class, all of which act on the same molecular target, Gal calls the distinction between biobetters and new chemical entities “very, very blurry.”

So why are so many companies still pursuing biosimilars?

“They’re hoping to thread the needle,” Dahiyat explains.

“Perhaps they believe they can leverage other elements of their organizations, or balance that risk across a portfolio of products.”

For an overview of eyeforpharma’s forecasting coverage, see Highlights from eyeforpharma’s Forecasting coverage.

For exclusive business insights, download eyeforpharma's Pharma Emerging Markets Report 2011-12 and Pharma Key Account Management Report 2011-12.

For all the latest business analysis and insight for the pharma industry, sign up to eyeforpharma’s newsletters and follow us on Twitter.

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Forecasting for licensed compounds

Peter Mansell — Fri, 14 Oct 2011 20:25:14 +0000

Précis:

Peter Mansell examines the impact of heavier in-licensing/out-licensing traffic on pharma forecasting

Outsourcing, partnering, risk-sharing: These are increasingly the modus operandi of the biopharmaceutical industry as it re-examines its business model and addresses demand for more cost-efficient and -effective innovation, fit for purpose in health systems under financial and demographic strain.

More focused R&D strategies that prune out dead wood or high-risk therapy areas are leaving pipeline gaps that make management and investors nervous.

The patent cliff is swallowing dependable revenue streams that can no longer be replaced with a new generation of big-hitters, as emphasis shifts to targeted therapies and niche indications.

With access to capital thinning out and development programs becoming more complex, protracted and demanding, there is growing pressure, too, on biotechnology companies to find partners for viable compounds while they are still afloat.

And academic researchers are looking to translational research and relationships with an industry hungry to counteract squeezes on public funding.

These factors combined add up to heavier in-licensing/out-licensing traffic in the life sciences—and all of them inevitably have an impact on pharmaceutical forecasting, at both ends of the equation.

Pipeline opportunities

Whether in-licensing is a long-term solution to big pharma’s much-discussed R&D drought is a matter for debate.

Not everyone is as bullish as the analysts at Morgan Stanley who last year suggested that pharmaceutical companies could triple their returns by exiting early-stage drug development and reinvesting in outsourcing. (For more on outsourcing, see Will big pharma become a collection of marketing and distribution firms?.)

In fact, the industry appears to have become more circumspect about what it will buy into, albeit not averse to paying a premium for real value.

High prices for some early-stage biotech assets, expensive failures in the latter stages of clinical development and the effects of global recession have all encouraged closer scrutiny of pipeline opportunities, whether internal and external.

Writing in Innovations in Pharmaceutical Technology last summer, Tibor Papp, head of corporate advisory at PharmaVentures Ltd, highlighted a fall of over one third in collaborative deals for pharmaceutical assets between 2005 and 2009.

What was licensed in, though, could be handsomely rewarded.

In 2000, Papp noted, less than 10 percent of all licensing deals with published financials promised more than $100 million in upfront and milestone payments.

By 2009, the proportion of these high-vale agreements had jumped to over 70 percent.

Even with the number of deals contracting, around 40 percent of pharmaceutical pipeline candidates were still coming from external sources, while a comparable proportion of sales in the marketplace were driven by in-licensed or acquired technologies.

More recently, PharmaVentures has highlighted a trend towards recovery.

While collaborative R&D deals continued to decline in volume and value during 2010, licensing activity was on the rise compared with 2009, even if the average value (excluding royalties) of licensing deals with disclosed financial information fell markedly from the high seen in that year.

The impact on forecasting

As Nic Talbot-Watt, managing director of Black Swan Analysis, points out, the impact on pharmaceutical forecasting will involve quite different agendas.

“The company that’s selling the asset obviously wants to get top dollar for it,” Talbot-Watt notes. For the company licensing in, though, the priority is to “pay as little as possible.”

As such, companies weighing up in-licensing opportunities will want to take a fresh look at the potential asset rather than extrapolating from any value attached to it by the vendor.

“In my experience, they start afresh,” comments Carla Peek, head of business modeling and analytics at Inpharmation.

“They commission their own models. We’ve never been presented with, ‘Here’s a model from the company we’re licensing from. How can we improve it?’”

For Talbot-Watt, this is probably a “bit of game play.”

Given the inevitable conflict of agendas, if a company can say it has used an external vendor, “it lends a little bit more credibility to their valuation.”

There are also practical reasons for sticking with what you know, Peek observes. Often different companies license different forecasting software.

“So somebody might have Forecast Architect and somebody might have Flexicast,” she says.

“They go with what they know and they present their results in the way that they always have presented them, because they have their standard templates and standard charts, and that is what management is used to.”

What the external forecast really comes down to, Peek observes, is fleshing out and corroborating a business strategy that will already be well advanced in house.

“The main thing is that they want to see this is going to be possible, it’s going to be a good opportunity,” she notes.

“And hopefully, by the time they are commissioning forecasts and market research, they already have a good sense that this is a good therapy area to go into and to plan a strategy around. They’re looking for a forecast that can validate what they’ve said.”

Market research

If the people making those decisions are not so familiar with the target therapy area, they will need to conduct market research to make sure they understand the key elements of the market they are moving into, such as treatment paradigms, market size and the adoption rates, Peek adds.

She believes there’s less market research done for in-licensed products than for in-house, “but they need to understand this. Otherwise, they’re going to make a bad decision.”

The level of information a client will want on a licensing opportunity will likely depend on the client’s internal proficiency and resources as well as where the product sits in the clinical development process.

So it may range from epidemiology and disease characteristics to a full-blown business case.

If a product is in Phase II trials, for example, there will generally be details of the clinical program and the therapeutic target, Talbot-Watt explains.

Black Swan will then work primarily on patient sizing and the physician management flow, to pin down where the product would fit in the marketplace.

Alternatively, the brief may be for comprehensive modeling, with first and second to market, uptake, benchmark analogues, etc.

“Other companies will want a full-blown business case,” Talbot-Watt adds.

“And part of that will be the epidemiology and the forecast, and another part could be SWOT analysis and things like that.”

New products closest to market are more likely to be me-toos, Peek observes, so those forecasts “may be driven by order of entry, because that’s going to be the biggest determinant of your market share.”

The process also calls for quite a lot of qualitative market research.

“If it’s a therapy area they’re not used to, they need to define the market size, treatment paradigms, adoption rates, the number of competitors,” Peek notes.

“It might be a huge market but it might be saturated.”

With in-house products, she adds, companies will spend much more money on quantitative market research, such as a lot of conjoint studies to define the target product profile and determine clinical endpoints.

“But with in-licensing you hope that’s already been defined,” she says.

Rapid forecasts

One thing both Peek and Talbot-Watt emphasize is the need to turn licensing forecasts around quickly, even within a couple of weeks.

“It’s competitive and some of their shareholders might be getting impatient because there are gaps in the pipeline,” Peek comments.

“So if they’re looking for opportunities, it’s usually a very rapid forecast.”

It also has to be affordable since, when making those decisions, executives don’t want to spend a lot of money, either.

“They can’t justify spending hundreds of thousands on huge conjoint analyses,” Peek observes.

“And they don’t need to, because the product profile has probably already been defined.”

With an in-house asset, the company is likely to have planned out its timelines at the beginning of the year and set objectives.

As Talbot-Watt points out, forecasting for an in-licensing opportunity must be not only time-sensitive but sufficiently robust to form the basis of an investment decision.

With out-licensing, the process tends to be little more extended, as “it’s their asset and they know what they can do with it.”

Essentially, forecasters should be applying the same degree of rigor to licensing opportunities as they would to an in-house product.

They may have to be much more explicit with the sources and references they use, though, “because often if they’re publishing the deal, they want data they can actually stand on,” Talbot-Watt comments.

Forecasters may also need to do a little bit more of the legwork in terms of disease pathology for in-licensing, as they will not have access to medical staff in the originating company.

One marked difference, Talbot-Watt notes, is that an in- or out-licensed product will require input around deal structures and financing rather than just internal components such as R&D investment.

“They have to structure some sort of deal,” she says.

“And depending on the nature of the deal, they’ll probably want to put some sort of financial analysis into the models.”

The way these deals are structured—with their upfront payments, milestones for approval filings and/or product launches, and further payments or royalties tied to preset sales projections—is becoming increasingly complex.

This reflects a trend both toward product originators taking more of a stake in their discoveries and toward pharmaceutical companies wanting to spread more of the risks of drug development.

Whereas companies used to buy assets outright, there now seems to be more willingness to partner, some of it driven by biotechs or universities wanting more of a working relationship.

“It’s their intellectual property and they sort of know how to develop it,” says Talbot-Watt.

“They just need the cash and a little bit of commercial direction.”

Advanced forecasting techniques

With pharmaceutical companies paying closer attention to cost-efficiency and productivity in R&D, there is more demand for advanced forecasting techniques that give a clearer idea of value.

“Previously forecasters didn’t need to incorporate NPVs [net present values] into their forecasts,” Peek comments. “Now it’s becoming the norm.”

These forecasters “were certainly doing scenario modeling but sensitivity analysis, risk analysis—that wasn’t the norm. Now most of our forecasts are going out with NPVs and with sensitivity analyses, risk analyses, feasibility.”

In the near future, Peek predicts, it could be that pricing and reimbursement strategies will enter the equation, which is at the moment a different department.

But she believes it is coming to the stage where these two are going to have to start contracting.

One further trend that may affect forecasting requirements for in- or out-licensed products in years to come is that these assets are being traded much later in the development cycle.

A lot of companies, Talbot-Watt says, are on the rebound from “investing in very early-stage assets that never got anywhere. We’re seeing things that are either in Phase III or they’ve already completed their Phase III and are going through registration.”

This could be “a bit of a poker game,” she speculates, one reflected in the speed of analysis required now in product valuations: “They leave it until a pivotal trial has reported favorably and then they jump in. But then, of course, it’s a dash to the finish line.”

For an overview of eyeforpharma’s forecasting coverage, see Highlights from eyeforpharma’s Forecasting coverage.

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Forecasting the future of biologics

Peter Mansell — Thu, 15 Sep 2011 11:40:52 +0000

Précis:

Peter Mansell reports on how to balance complexity and predictability when forecasting for biologics

The growing presence of biologics in R&D pipelines and on the pharmaceutical market has brought with it issues of complexity and controversy around product composition, variability and reproducibility, safety, modes of administration, and costs to healthcare systems.

All of which suggests that forecasting for these therapies is a much trickier proposition than for small-molecule drugs.

Not necessarily so, says Florian Turk, executive director and head of Global Health Economics & Outcomes Research at Novartis Pharma AG.

Turk’s focus is on market access and health technology assessment scenarios that feed into estimates of product uptake.

The overarching challenge in forecasting MA potential is accuracy, particularly given the proliferation of customers and stakeholders acting according to their particular business rationale and budget, he points out.

The complexity of this process is “certainly increasing,” Turk comments.

But it is not automatically more of a problem for biologics than for small-molecule drugs.

For one thing, biologics tend to be better characterized than their small-molecule equivalents.

“Sometimes, forecasting for specialties is now easier for us than in primary care,” Turk says.

“As part of your business preparation, it is easier to see what the likely restrictions are and what the likely offerings are in terms of the patient populations to be targeted.”

Nor, he says, does the relative complexity of biologics necessarily muddy patient pathways, at least from a forecasting perspective.

A better-defined patient population will make these pathways easier to plot. (For more on biologics, see ‘Patent expiration: Innovate or die’ and ‘Dr. Bates Talkback: How to mount an effective defense against generics’.)

Moreover, primary care products sold at premium prices are at the same risk of factors that complicate the treatment regime, such as prior authorization criteria, protocols, or demand for extra data to underpin duration of therapy, Turk notes.

So the basic rules of engagement are already in place.

Tipping toward complexity

What may tip biologics toward complexity is treatment response, particularly when products are bundled with companion diagnostics and the treatment regime depends on response analyses that may thin out the available patient population. (For more on companion diagnostics, see ‘New challenges and techniques in forecasting’ and ‘Personalized medicine: Regulating companion diagnostics’.)

“First of all, you need a good forecast of response, of patient population, of genotype,” Turk explains.

“Secondly, companion diagnostics, and these different starting and stopping rules, are usually developed alongside the drug.”

So the uncertainty resides not so much in the nature of biologics as in the business models developed for them.

These may involve factors where “we don’t have many market analogues”, Turk notes.

Potential variables include how accurate a companion diagnostic may be; whether a suitable diagnostic will be available/accepted and, if so, in which markets; and the greater likelihood that biologics will be subject to risk-sharing or pay-for-performance schemes. (For more on risk sharing, see ‘Managing market uncertainty: Is risk sharing the answer?’ and ‘Market access: Risk sharing and alternative pricing schemes’.)

In general, and despite the ongoing debate around pricing, HTA conditions for biologics are not fundamentally different from those for small-molecule drugs, Turk says.

All the same, actual product uptake will depend on ‘real-life’ treatment effectiveness.

“When you do the forecast, you have some idea about the product’s efficacy and safety,” Turk comments. “But you don’t know what the effectiveness will be.”

Generic entry

With the regulatory framework for biosimilars starting to clarify, biologics forecasts also need to factor in the potential impact of generic entry down the line.

Turk is not convinced, though, that the competitive threat is any less measurable than for mainstream generics.

There may be more uncertainty from a technological viewpoint, depending on the methods of synthesis or production used, he points out.

But the same factors can lead to marked variability between biologics themselves.

“In the end, when you forecast you have the same assumptions: How many players do we expect to enter the market? How many of them do we expect to enter at risk?” (For more on generics, see ‘Forecasting for generic erosion rates’.)

Another consideration is whether biologics, particularly those sold at high prices, have a place in the emerging markets that will increasingly drive pharmaceutical industry revenue and profits.

Here also, Turk sees no black-and-white distinction between cutting-edge therapies and small-molecule drugs.

The superior targeting available with many biologics means “there is a much stronger case for a limited number of patients in a number of emerging growth markets,” Turk says.

It really depends on the stage of development. There are emerging markets that have evolved to the point where they can afford additional treatment solutions for small patient populations in real need.

Then there are less developed countries where even conventional branded drugs have only a very small market share.

In South Africa, for example, the issue is not so much the type of molecule as whether it is branded or generic, Turk observes.

For a mainstream drug with a large patient population or for a biologic with a more targeted population, “In the end, what matters for the market is overall budget impact,” he says.

Familiarity is also easing the challenges of forecasting for biologics.

With the first generation of products, such as the monoclonal antibody Remicade, it was “really unknown territory,” Turk comments.

Now that a number of analogies are available in different countries, there is a much better understanding of how the market functions.

Accordingly, much of the uncertainty has been removed from biologics forecasting, Turk believes.

Rather, the scales have tilted so that “a lot of uncertainty has been added to the conventional products as well.”

On this more level playing field, he adds, “It’s all about predicting the changes in the external environment.”

For all the latest on forecasting, join the sector’s other key players at the 5th Annual Forecasting Excellence conference on October 4-6 in Boston.

For an overview of eyeforpharma’s forecasting coverage, see ‘Highlights from eyeforpharma’s Forecasting coverage’.

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