Interpretation of diagnostic data: 3. How to do it with a simple table (part B).

The following guidelines are useful if you want to "do it with a simple table" (Table IV): First, identify the sensitivity and specificity of the sign, symptom or diagnostic test you plan to use. Many are already in the literature, and subspecialists should either know them for their field or be able to track them down for you. Depending on whether you are considering a sign, a symptom or a diagnostic laboratory test, you will want to track down a clinical subspecialist, a radiologist, a pathologist and so on. Start your table with a total of 1000 patients, as shown in location (a + b + c + d) of panel A. Using the information you have about the patient before you apply the diagnostic test, estimate the patient''s pretest likelihood (prevalence or prior probability) of the target disorder -- let''s say 10%. Take this proportion of the total (100) and place it in location (a + c); the remaining 900 patients go in location (b + d) (panel B). Multiply (a + c) (100) by the sensitivity of the diagnostic test (let''s say 83%) and place the result (83) in cell a and the difference (17) in cell c; similarly, multiply (b + d) (900) by the specificity of the diagnostic test (let''s say 91%) and place the result (819) in cell d and the difference (81) in cell b (panel C). If (a + b) and (c + d) do not add up to 1000, you will know you have made a mistake. You can now calculate the positive predictive value, a/(a + b), and the negative predictive value, d/(c + d), as shown in panel D. You have now reached a level of understanding a fair bit beyond the rule-in/rule-out strategy discussed in part 1 of our series. Furthermore, you can already do more than most clinicians, so you may want to stop here, at least for a while. On the other hand, you may want to go further and learn how to handle slightly more complex tables with multiple cut-off points. In the next article you will find more powerful ways to take advantage of the degree of positivity and negativity of diagnostic test results.     

Interpretation of diagnostic data: 4. How to do it with a more complex table.

A more complex table is especially useful when a diagnostic test produces a wide range of results and your patient''s levels are near one of the extremes. The following guidelines will be useful: Identify the several cut-off points that could be used. Fill in a complex table along the lines of Table I, showing the numbers of patients at each level who have and do not have the target disorder. Generate a simple table for each cut-off point, as in Table II, and determine the sensitivity (TP rate) and specificity (TN rate) at each of them. Select the cut-off point that makes the most sense for your patient''s test result and proceed as in parts 2 and 3 of our series. Alternatively, construct an ROC curve by plotting the TP and FP rates that attend each cut-off point. If you keep your tables and ROC curves close at hand, you will gradually accumulate a set of very useful guides. However, if you looked very hard at what was happening, you will probably have noticed that they are not very useful for patients whose test results fall in the middle zones, or for those with just one positive result of two tests; the post-test likelihood of disease in these patients lurches back and forth past 50%, depending on where the cut-off point is. We will show you how to tackle this problem in part 5 of our series. It involves some maths, but you will find that its very powerful clinical application can be achieved with a simple nomogram or with some simple calculations.     

Credit Default Swaps Drawup Networks: Too Interconnected to Be Stable?

We analyse time series of CDS spreads for a set of major US and European institutions in a period overlapping the recent financial crisis. We extend the existing methodology of -drawdowns to the one of joint -drawups, in order to estimate the conditional probabilities of spike-like co-movements among pairs of spreads. After correcting for randomness and finite size effects, we find that, depending on the period of time, 50% of the pairs or more exhibit high probabilities of joint drawups and the majority of spread series are trend-reinforced, i.e. drawups tend to be followed by drawups in the same series. We then carry out a network analysis by taking the probability of joint drawups as a proxy of financial dependencies among institutions. We introduce two novel centrality-like measures that offer insights on how both the systemic impact of each node as well as its vulnerability to other nodes'' shocks evolve in time.     

Characterizing the Impact of Category Uncertainty on Human Auditory Categorization Behavior

Categorization is an important cognitive process. However, the correct categorization of a stimulus is often challenging because categories can have overlapping boundaries. Whereas perceptual categorization has been extensively studied in vision, the analogous phenomenon in audition has yet to be systematically explored. Here, we test whether and how human subjects learn to use category distributions and prior probabilities, as well as whether subjects employ an optimal decision strategy when making auditory-category decisions. We asked subjects to classify the frequency of a tone burst into one of two overlapping, uniform categories according to the perceived tone frequency. We systematically varied the prior probability of presenting a tone burst with a frequency originating from one versus the other category. Most subjects learned these changes in prior probabilities early in testing and used this information to influence categorization. We also measured each subject''s frequency-discrimination thresholds (i.e., their sensory uncertainty levels). We tested each subject''s average behavior against variations of a Bayesian model that either led to optimal or sub-optimal decision behavior (i.e. probability matching). In both predicting and fitting each subject''s average behavior, we found that probability matching provided a better account of human decision behavior. The model fits confirmed that subjects were able to learn category prior probabilities and approximate forms of the category distributions. Finally, we systematically explored the potential ways that additional noise sources could influence categorization behavior. We found that an optimal decision strategy can produce probability-matching behavior if it utilized non-stationary category distributions and prior probabilities formed over a short stimulus history. Our work extends previous findings into the auditory domain and reformulates the issue of categorization in a manner that can help to interpret the results of previous research within a generative framework.     

Doctors' attitudes to risk in difficult clinical decisions: application of decision analysis in hepatobiliary disease.

Twelve doctors with special training in hepatology independently reviewed two to five cases each from a group of seven cases of complicated hepatobiliary problems. A doctor''s willingness to take risks to improve his patients'' health was quantified by a wagering technique based on the probability of achieving a successful intervention. These probabilities were then used to calculate "utilities," which represented the average opinion of the doctors about the relative worth of each of six predefined states of health. The results showed that, in the context of risky decisions for severely ill patients, a year of life was considered by the doctors to be worth 44% of a full recovery; being mobile for that year increased this value to 57%. Survival for up to five years with restricted mobility was considered to be worth 70% of a full recovery and the ability to work during that period increased this value to 85%. It is concluded that in clinical decision making the uncertainty and preferences implicit in a course of action can be quantified and thus made explicit.     

Training in medical informatics. The use of computers for diagnostic purposes

Part of a blockcourse on medical informatics is presented; this course is intended for medical students. It is shown how medical students are introduced to the study of the role of computers for diagnostic purposes. The course consists of an oral presentation which introduces the student to the subject, and of practical work on systems in order to more fully comprehend the topics explained in the oral part of the blockcourse. In the oral presentation the student is introduced to various concepts that are used in computer-aided diagnosis. A critical review of the possibilities of computer use for diagnostic purposes is given. A system is presented, with which the student can work interactively. It consists of a database of patients, referred to the hospital because of suspected congenital heart disorder. Bayes' rule and diagnostic tree decision schemes are available to the student to acquaint himself with the subject. The ways he can work with this system are explained. The course is given regularly (every 4 months) to medical students and is well appreciated.     

Introducing the Internet.

The benefits to medical practitioners of using the Internet are growing rapidly as the Internet becomes easier to use and ever more biomedical resources become available on line. The Internet is the largest computer network in the world; it is also a virtual community, larger than many nation states, with its own rules of behaviour or "netiquette." There are several types of Internet connection and various ways of acquiring a connection. Once connected, you can obtain, free of charge, programs that allow easy use of the Internet''s resources and help on how to use these resources; you can access many of these resources through the hypertext references in the on line version of this series (go to http:@www.bmj.com/bmj/ to reach the electronic version). You can then explore the various methods for accessing, manipulating, or disseminating data on the Internet, such as electronic mail, telnet, file transfer protocol, and the world wide web. Results from a search of the world wide web for information on the rare condition of Recklinghausen''s neurofibromatosis illustrate the breadth of medical information available on the Internet.     

Haplotype fine mapping by evolutionary trees

To refine the location of a disease gene within the bounds provided by linkage analysis, many scientists use the pattern of linkage disequilibrium between the disease allele and alleles at nearby markers. We describe a method that seeks to refine location by analysis of "disease" and "normal" haplotypes, thereby using multivariate information about linkage disequilibrium. Under the assumption that the disease mutation occurs in a specific gap between adjacent markers, the method first combines parsimony and likelihood to build an evolutionary tree of disease haplotypes, with each node (haplotype) separated, by a single mutational or recombinational step, from its parent. If required, latent nodes (unobserved haplotypes) are incorporated to complete the tree. Once the tree is built, its likelihood is computed from probabilities of mutation and recombination. When each gap between adjacent markers is evaluated in this fashion and these results are combined with prior information, they yield a posterior probability distribution to guide the search for the disease mutation. We show, by evolutionary simulations, that an implementation of these methods, called "FineMap," yields substantial refinement and excellent coverage for the true location of the disease mutation. Moreover, by analysis of hereditary hemochromatosis haplotypes, we show that FineMap can be robust to genetic heterogeneity.     

Diagnostic schemes for fine needle aspirates of breast masses

A comparison was made of four statistically based schemes for classifying epithelial cells from 243 fine needle aspirates of breast masses as benign or malignant. Two schemes were computer-generated decision trees and two were user generated. Eleven cytologic characteristics described in the literature as being useful in distinguishing benign from malignant breast aspirates were assessed on a scale of 1 to 10, with 1 being closest to that described as benign and 10 to that described as malignant. The original computer-generated dichotomous decision tree gave 6 false negatives and 12 false positives on the data set; another tree generated from the current data improved performance slightly, with 5 false negatives and 10 false positives. Maximum diagnostic overlap occurred at the cut-point of the original dichotomous tree. The insertion of a third node evaluating additional parameters resulted in one false negative and seven false positives. This performance was matched by summing the scores of the eight characteristics that individually were most effective in separating benign from malignant. We conclude that, while statistically designed, computer-generated dichotomous decision trees identify a starting sequence for applying cytologic characteristics to distinguish between benign and malignant breast aspirates, modifications based on human expert knowledge may result in schemes that improve diagnostic performance.     

Interpretation of diagnostic data: 5. How to do it with simple maths.

The use of simple maths with the likelihood ratio strategy fits in nicely with our clinical views. By making the most out of the entire range of diagnostic test results (i.e., several levels, each with its own likelihood ratio, rather than a single cut-off point and a single ratio) and by permitting us to keep track of the likelihood that a patient has the target disorder at each point along the diagnostic sequence, this strategy allows us to place patients at an extremely high or an extremely low likelihood of disease. Thus, the numbers of patients with ultimately false-positive results (who suffer the slings of labelling and the arrows of needless therapy) and of those with ultimately false-negative results (who therefore miss their chance for diagnosis and, possibly, efficacious therapy) will be dramatically reduced. The following guidelines will be useful in interpreting signs, symptoms and laboratory tests with the likelihood ratio strategy: Seek out, and demand from the clinical or laboratory experts who ought to know, the likelihood ratios for key symptoms and signs, and several levels (rather than just the positive and negative results) of diagnostic test results. Identify, when feasible, the logical sequence of diagnostic tests. Estimate the pretest probability of disease for the patient, and, using either the nomogram or the conversion formulas, apply the likelihood ratio that corresponds to the first diagnostic test result. While remembering that the resulting post-test probability or odds from the first test becomes the pretest probability or odds for the next diagnostic test, repeat the process for all the pertinent symptoms, signs and laboratory studies that pertain to the target disorder. However, these combinations may not be independent, and convergent diagnostic tests, if treated as independent, will combine to overestimate the final post-test probability of disease. You are now far more sophisticated in interpreting diagnostic tests than most of your teachers. In the last part of our series we will show you some rather complex strategies that combine diagnosis and therapy, quantify our as yet nonquantified ideas about use, and require the use of at least a hand calculator.     

Self-organizing tree-growing network for the classification of protein sequences.

The self-organizing tree algorithm (SOTA) was recently introduced to construct phylogenetic trees from biological sequences, based on the principles of Kohonen''s self-organizing maps and on Fritzke''s growing cell structures. SOTA is designed in such a way that the generation of new nodes can be stopped when the sequences assigned to a node are already above a certain similarity threshold. In this way a phylogenetic tree resolved at a high taxonomic level can be obtained. This capability is especially useful to classify sets of diversified sequences. SOTA was originally designed to analyze pre-aligned sequences. It is now adapted to be able to analyze patterns associated to the frequency of residues along a sequence, such as protein dipeptide composition and other n-gram compositions. In this work we show that the algorithm applied to these data is able to not only successfully construct phylogenetic trees of protein families, such as cytochrome c, triosephophate isomerase, and hemoglobin alpha chains, but also classify very diversified sequence data sets, such as a mixture of interleukins and their receptors.     

An adaptive trial design to optimize dose-schedule regimes with delayed outcomes

This paper proposes a two-stage phase I-II clinical trial design to optimize dose-schedule regimes of an experimental agent within ordered disease subgroups in terms of the toxicity-efficacy trade-off. The design is motivated by settings where prior biological information indicates it is certain that efficacy will improve with ordinal subgroup level. We formulate a flexible Bayesian hierarchical model to account for associations among subgroups and regimes, and to characterize ordered subgroup effects. Sequentially adaptive decision-making is complicated by the problem, arising from the motivating application, that efficacy is scored on day 90 and toxicity is evaluated within 30 days from the start of therapy, while the patient accrual rate is fast relative to these outcome evaluation intervals. To deal with this in a practical manner, we take a likelihood-based approach that treats unobserved toxicity and efficacy outcomes as missing values, and use elicited utilities that quantify the efficacy-toxicity trade-off as a decision criterion. Adaptive randomization is used to assign patients to regimes while accounting for subgroups, with randomization probabilities depending on the posterior predictive distributions of utilities. A simulation study is presented to evaluate the design's performance under a variety of scenarios, and to assess its sensitivity to the amount of missing data, the prior, and model misspecification.     

Tree-average distances on certain phylogenetic networks have their weights uniquely determined

ABSTRACT: A phylogenetic network N has vertices corresponding to species and arcs corresponding to direct genetic inheritance from the species at the tail to the species at the head. Measurements of DNA are often made on species in the leaf set, and one seeks to infer properties of the network, possibly including the graph itself. In the case of phylogenetic trees, distances between extant species are frequently used to infer the phylogenetic trees by methods such as neighbor-joining. This paper proposes a "tree-average" distance for networks more general than trees. The notion requires a "weight" on each arc measuring the genetic change along the arc. For each displayed tree the distance between two leaves is the sum of the weights along the path joining them. At a hybrid vertex, each character is inherited from one of its parents. We will assume that for each hybrid there is a probability that the inheritance of a character is from a specified parent. Assume that the inheritance events at different hybrids are independent. Then for each displayed tree there will be a probability that the inheritance of a given character follows the tree; this probability may be interpreted as the probability of the tree. The "tree-average" distance between the leaves is defined to be the expected value of their distance in the displayed trees. For a class of rooted networks that includes rooted trees, it is shown that the weights and the probabilities at each hybrid vertex can be calculated given the network and the tree-average distances between the leaves. Hence these weights and probabilities are uniquely determined. The hypotheses on the networks include that hybrid vertices have indegree exactly 2 and that vertices that are not leaves have a tree-child.     

Nuclear power: levels of safety

The rise and fall of the nuclear power industry in the United States is a well-documented story with enough socio-technological conflict to fill dozens of scholarly, and not so scholarly, books. Whatever the reasons for the situation we are now in, and no matter how we apportion the blame, the ultimate choice of whether to use nuclear power in this country is made by the utilities and by the public. Their choices are, finally, based on some form of risk-benefit analysis. Such analysis is done in well-documented and apparently logical form by the utilities and in a rather more inchoate but not necessarily less accurate form by the public. Nuclear power has failed in the United States because both the real and perceived risks outweigh the potential benefits. The national decision not to rely upon nuclear power in its present form is not an irrational one. A wide ranging public balancing of risk and benefit requires a classification of risk which is clear and believable for the public to be able to assess the risks associated with given technological structures. The qualitative four-level safety ladder provides such a framework. Nuclear reactors have been designed which fit clearly and demonstrably into each of the possible qualitative safety levels. Surprisingly, it appears that safer may also mean cheaper. The intellectual and technical prerequisites are in hand for an important national decision. Deployment of a qualitatively different second generation of nuclear reactors can have important benefits for the United States. Surprisingly, it may well be the "nuclear establishment" itself, with enormous investments of money and pride in the existing nuclear systems, that rejects second generation reactors. It may be that we will not have a second generation of reactors until the first generation of nuclear engineers and nuclear power advocates has retired.     

The probability of topological concordance of gene trees and species trees

The concordance of gene trees and species trees is reconsidered in detail, allowing for samples of arbitrary size to be taken from the species. A sense of concordance for gene tree and species tree topologies is clarified, such that if the "collapsed gene tree" produced by a gene tree has the same topology as the species tree, the gene tree is said to be topologically concordant with the species tree. The term speciodendric is introduced to refer to genes whose trees are topologically concordant with species trees. For a given three-species topology, probabilities of each of the three possible collapsed gene tree topologies are given, as are probabilities of monophyletic concordance and concordance in the sense of N. Takahata (1989), Genetics 122, 957-966. Increasing the sample size is found to increase the probability of topological concordance, but a limit exists on how much the topological concordance probability can be increased. Suggested sample sizes beyond which this probability can be increased only minimally are given. The results are discussed in terms of implications for molecular studies of phylogenetics and speciation.     

Constructing and counting phylogenetic invariants.

The method of invariants is an approach to the problem of reconstructing the phylogenetic tree of a collection of m taxa using nucleotide sequence data. Models for the respective probabilities of the 4m possible vectors of bases at a given site will have unknown parameters that describe the random mechanism by which substitution occurs along the branches of a putative phylogenetic tree. An invariant is a polynomial in these probabilities that, for a given phylogeny, is zero for all choices of the substitution mechanism parameters. If the invariant is typically non-zero for another phylogenetic tree, then estimates of the invariant can be used as evidence to support one phylogeny over another. Previous work of Evans and Speed showed that, for certain commonly used substitution models, the problem of finding a minimal generating set for the ideal of invariants can be reduced to the linear algebra problem of finding a basis for a certain lattice (that is, a free Z-module). They also conjectured that the cardinality of such a generating set can be computed using a simple "degrees of freedom" formula. We verify this conjecture. Along the way, we explain in detail how the observations of Evans and Speed lead to a simple, computationally feasible algorithm for constructing a minimal generating set.     

Gene patents and capital investment

Will the US Supreme Court''s ruling that genes can no longer be patented in the USA boost venture capital investment into biotech and medical startup companies?Three years ago, Noubar Afeyan, managing partner and CEO of Flagship Ventures, an early-stage venture capital firm in Cambridge, Massachusetts, USA, was working with a biotech start-up company developing techniques for BRCA gene testing for breast cancer risk that avoided the patents held by Myriad Genetics, a molecular diagnostics company in Salt Lake City (Utah, USA) and the only operator in the field. However, despite the promise of the start-up''s techniques, investors were put off by Myriad''s extensive patent portfolio and fiercely defensive tactics: “A lot of investors were simply not willing to take that chance, even though our technology was superior in many ways and patentably different,” Afeyan said. The effort to launch the start-up ultimately failed.…it is also not clear how the Supreme Court''s ruling will affect the […] industry at large, now that one of the most contested patents for a human gene has been ruled invalidAfeyan believes the prospects for such start-ups improved on the morning of 13 June 2013 when the US Supreme Court ruled in an unanimous vote that Myriad''s fundamental patents on the BRCA1 and BRCA2 genes themselves are invalid, opening up the field to new competitors. The court''s ruling, however, validated Myriad''s patents for BRCA cDNA and methods-of-use.The court''s decision comes at a time when venture capital investment into the life sciences is projected to decline in the years ahead. Some believe that the court''s decision sets a precedent and could provide a boost for products, diagnostics and other tests under development that would have been legally difficult in the light of existing patents on human and other DNA sequences.The US Patent Office issued the original patents for the BRCA 1 and BRCA2 genes in 1997 and 1998 for the US National Institute of Environmental Health Services, the University of Utah and Myriad Genetics. One year earlier, Myriad had launched its first diagnostic test for breast cancer risk based on the two genes and has since aggressively defended it against both private and public competitors in court. Many universities and hospitals were originally offering the test for a lower cost, but Myriad forced them to stop and eventually monopolized BRCA-based diagnostics for breast cancer risk in the USA and several other countries.“Myriad did not create anything,” Justice Clarence Thomas wrote in the Supreme Court''s decision. “To be sure, it found an important and useful gene, but separating that gene from its surrounding genetic material is not an act of invention.” Even so, the court did uphold Myriad''s patents on the methodology of its test. Ron Rogers, a spokesman for the biotech firm, said the Supreme Court had “affirmed the patent eligibility of synthetic DNA and underscored the importance and applicability of method-of-use patents for gene-based diagnostic tests. Before the Supreme Court case we had 24 patents and 520 claims. After the Supreme Court decision, we still have 24 patents. […] [T]he number of our patent claims was reduced to 515. In the Supreme Court case itself, only nine of our 520 patent claims were at issue. Of the nine, the Supreme Court ruled that five were not patent-eligible and they ruled that four were patent-eligible. We still have strong intellectual property protection surrounding our BRCA test and the Supreme Court''s decision doesn''t change that.”Within hours of the ruling, capitalism kicked into high gear. Two companies, Ambry Genetics in Alieso Viejo, California, and Gene by Gene Ltd in Houston, Texas, USA, announced that they were launching tests for the BRCA1 and BRCA2 genes for less than the US$3,100 Myriad has been charging privately insured patients and US$2,795 for patients covered by Medicare—the government health plan for the elderly and disabled. Several other companies and universities also announced they would be offering BRCA testing.Entrepreneur Bennett Greenspan, a managing partner of Gene by Gene, explained that his company had been poised to offer BRCA testing if the Supreme Court ruled against Myriad. He said, “We had written a press release with our PR firm a month before the release of the Supreme Court with the intention that if the Supreme Court overruled the patent or invalidated the patent that we would launch right away and if they didn''t, we would just tear up the press release.” His company had previously offered BRCA gene testing in Israel based on guidelines from the European Union.Myriad Genetics has not given up defending its patents, however. On 9 and 10 July 2013, it slapped Ambry and Gene by Gene with lawsuits in the US District Court in Salt Lake City for allegedly infringing on patents covering synthetic DNA and methods-of-use related to the BRCA1 and BRCA2 genes. Rogers commented that the testing processes used by the firms “infringes 10 patents covering synthetic primers, probes and arrays, as well as methods of testing, related to the BRCA1 and BRCA2 genes.”On 6 August 2013, Ambry countersued Myriad, arguing that the company “continues a practice of using overreaching practices to wrongfully monopolize the diagnostic testing of humans'' BRCA1 and BRCA2 genes in the United States and to attempt to injure any competitor […] Due to Myriad''s anticompetitive conduct, customers must pay significantly higher prices for Myriad''s products in the relevant market, often nearly twice as high as the price of Ambry''s products and those of other competitors” [1].Just as the courts will have to clarify whether the competitors in this case infringe on Myriad''s patents, it is also not clear how the Supreme Court''s ruling will affect the biotech and diagnostics industry at large, now that one of the most contested patents for a human gene has been ruled invalid. In recent years, venture capital investment into the life sciences has been in decline. The National Venture Capital Association and the Medical Innovation & Competitiveness Coalition reported from a survey that, “An estimated funding loss of half a billion dollars over the next three years will cost America jobs at a time when we desperately need employment growth” [2]. The survey of 156 venture capital firms found that 39% of respondents said they had reduced investment in the life sciences during the previous three years, and the same proportion intended to do so in the next three years. “[US Food and Drug Administration] FDA regulatory challenges were identified as having the highest impact on these investment decisions,” the report states, adding that many investors intended to shift their focus from the US towards Europe and the Asia/Pacific region.Another report from the same groups explains how public policy involving the FDA and other players in “the medical innovation ecosystem”—including the US patent system, public agencies, tax policy, securities regulation, immigration laws and private groups such as insurers—affect the decisions of investors to commit to funding medical innovation [3].Some investors think that the court decision about the patentability of human DNA will increase confidence and help to attract investors back to the life sciencesSome investors think that the court decision about the patentability of human DNA will increase confidence and help to attract investors back to the life sciences. “The clarity is helpful because for the longest time people didn''t do things because of ambiguity about whether those patents would be enforceable,” Afeyan said. “It''s one thing to not do something because of a patent, it''s another to not do something because you know that they have patents but you''re not sure what it''s going to stop you from doing because it hasn''t been really fully fleshed out. Now I think it is reasonably well fleshed out and I think you will see more innovation in the space.”Others also appreciate the clarification from the Supreme Court about what is a patentable invention in regard to human genes and DNA. “The Myriad decision was a very solid reading of the underlying purpose of our patent law, which is to reward novel invention,” commented Patrick Chung, a partner with New Enterprise Associates, a venture capital firm in Menlo Park, California, which invested in 23andMe, a personal genomics company based in Mountain View (California, USA), and who serves on the 23andMe board.But not everyone agrees that the Supreme Court''s decision has provided clarity. “You could spin it and say that it was beneficial to create some certainty, but at the end of the day, what the Court did was reduce the scope of what you''re allowed to get patent claims on,” said Michael Schuster, a patent lawyer and Intellectual Property Partner and Co-Chair of the Life Sciences Group at Fenwick & West LLP in San Francisco, California, USA. “It''s going to be a continuing dance between companies, smart patent lawyers, and the courts to try to minimize the impact of this decision.”Kevin Noonan, a molecular biologist and patent lawyer with McDonnell Boehnen Hulbert & Berghoff LLP in Chicago, Illinois, USA, commented that he does not expect the Supreme Court decision will have much of an impact on venture investments or anything else. “This case comes at a time fortunately when biotechnology is mature enough so that the more pernicious effects of the decision are not going to be quite as harmful as they would if this had happened ten, 15 or 20 years ago,” he said. “We''re now in the ‘post-genomic'' era; since the late ‘90s and turn of the century, the genomic and genetic data from the Human Genome Project have been on publicly available databases. As a consequence, if a company didn''t apply for a patent before the gene was disclosed publicly, it certainly is not able to apply for a patent now. The days of obtaining these sequences and trying to patent them are behind us.”Noonan also noted that the Myriad Genetics patents were due to expire in 2014–2015 anyway. “Patents are meaningless if you can''t enforce them. And when they expire, you can no longer enforce them. So it really isn''t an impediment to genetic testing now,” he explained. “What the case illustrates is a disconnect between scientists and lawyers. That''s an old battle.”George Church, professor of genetics at Harvard Medical School (Boston, Massachusetts, USA) and Director of the Personal Genome Project, maintains that the Supreme Court decision will have minimal influence on the involvement of venture capitalists in biotech. “I think it''s a non-issue. It''s basically addressing something that was already dead. That particular method of patenting or trying to patent components of nature without modification was never really a viable strategy and in a particular case of genes, most of the patents in the realm of bio-technology have added value to genes and that''s what they depend on to protect their patent portfolio—not the concept of the gene itself,” he said. “I don''t know of any investor who is freaked out by this at all. Presumably there are some, because the stock oscillates. But you can get stock to oscillate with all kinds of nonsense. But I think the sober, long-term investors who create companies that keep innovating are not impacted.”Church suggests that the biggest concern for Myriad now is whole-gene sequencing, rather than the Supreme Court''s decision. “Myriad should be worrying about the new technology, and I''m sure they''ve already considered this. The new technology allows you to sequence hundreds of genes or the whole genome for basically the price they''ve been charging all along for two genes. And from what I understand, they are expanding their collection to many genes, taking advantage of next generation sequencing as other companies have already,” he said.Whatever its consequences in the US, the Supreme Court''s decision will have little impact on other parts of the world, notably Europe, where Myriad also holds patents on the BRCA genes in several countries. Gert Matthijs, Head of the Laboratory for Molecular Diagnostics at the Centre for Human Genetics in Leuven, Belgium, says that even though the US Supreme Court has invalidated the principle of patenting genes in America, the concept remains in Europe and is supported by the European Parliament and the European Patent Convention. “Legally, nothing has changed in Europe,” he commented. “But there is some authority from the US Supreme Court even if it''s not legal authority in Europe. Much of what has been used as arguments in the Supreme Court discussions has been written down by the genetics community in Europe back in 2008 in the recommendations on behalf of the European Society for Human Genetics. The Supreme Court decision is something that most of us in Europe would agree upon only because people have been pushing towards protecting the biotech industry that the pendulum was so way out in Europe.”Benjamin Jackson, Senior Director of legal affairs at Myriad Genetics, commented that Myriad holds several patents in Europe that are not likely to be affected by the Supreme Court''s ruling. “The patent situation both generally and for Myriad is a lot clearer in Europe. The European Union Biotech Directive very clearly says that isolated DNA is patentable even if it shares the same sequence as natural DNA,” he said. “Right now, it''s pretty uncontroversial, or at least it''s well settled law basically in Europe that isolated DNA is patentable.” However, while the Directive states that “biological material which is isolated from its natural environment or produced by means of a technical process” might be patentable “even if it previously occurred in nature”, the European Patent Office (EPO) in Munich, Germany, requires that the subject matter is an inventive step and not just an obvious development of existing technology and that the industrial application and usefulness must be disclosed in the application.Myriad has opened a headquarters in Zurich and a lab in Munich during the past year, hoping to make inroads in Europe. In some EU countries, Myriad offers its BRCA test as part of cancer diagnosis. In other countries, BRCA testing is conducted at a fraction of what Myriad charges in the USA, either because institutions ignore the patents that are not enforced in their jurisdictions, or because these countries, such as Belgium, were not included in the patent granted by the European Patent Office. Moreover, in various countries BRCA testing is only available through the healthcare system and only as part of a more extensive diagnosis of cancer risk. In addition, as Matthijs commented, “[t]he healthcare system in Europe is very heterogeneous and that''s also of course a big impediment for a big laboratory to try and conquer Europe because you have to go through different reimbursement policies in different countries and that''s not easy.”Ultimately, it seems the Supreme Court''s decision might turn out to have little impact on biotech firms in either the USA or Europe. Technological advances, in particular new sequencing technologies, might render the issue of patenting individual genes increasingly irrelevant.     

Augmenting superpopulation capture-recapture models with population assignment data

Summary Ecologists applying capture–recapture models to animal populations sometimes have access to additional information about individuals' populations of origin (e.g., information about genetics, stable isotopes, etc.). Tests that assign an individual's genotype to its most likely source population are increasingly used. Here we show how to augment a superpopulation capture–recapture model with such information. We consider a single superpopulation model without age structure, and split each entry probability into separate components due to births in situ and immigration. We show that it is possible to estimate these two probabilities separately. We first consider the case of perfect information about population of origin, where we can distinguish individuals born in situ from immigrants with certainty. Then we consider the more realistic case of imperfect information, where we use genetic or other information to assign probabilities to each individual's origin as in situ or outside the population. We use a resampling approach to impute the true population of origin from imperfect assignment information. The integration of data on population of origin with capture–recapture data allows us to determine the contributions of immigration and in situ reproduction to the growth of the population, an issue of importance to ecologists. We illustrate our new models with capture–recapture and genetic assignment data from a population of banner‐tailed kangaroo rats Dipodomys spectabilis in Arizona.