Cyprotex Share Discussion Threads

[buywell3] 10/12/2015 22:42

Congratulations and celebrations ..... that AstraZeneca are involved can only be good



Cyprotex wins Bionow Company of the Year 2015

30th November 2015


Cyprotex have been announced as 2015 Company of the Year at the 14th Bionow Annual Awards ceremony which was held on 26th November 2015. The event invites the most prominent businesses, products, technologies and individuals leading the life science industry in the North of the UK.

The 2015 Company of the Year award, which is sponsored by AstraZeneca, is given in recognition of Cyprotex’s achievements in the past year, with special consideration to business milestones like the Company’s global expansion and return to profitability, as well as development of novel technologies and research that contribute to the scientific community.

Dr. Anthony Baxter, CEO of Cyprotex, commented, “We are honoured to win the Bionow Company of the Year award. This is testament to the efforts of all our staff. Their commitment, drive and expertise have been instrumental in the growth and success of the Company.”

[buywell2] 09/12/2015 22:25

‘Post-antibiotic era’ looms amid unregulated drugs market – UK govt review
20 Nov, 2015 15:04

Unregulated antibiotic sales in pharmacies and online are fueling the rise of deadly “superbug̶1; bacteria as the world sits on the cusp of an “antibiotic apocalypse,” according to a UK government-commissioned report.

Antibiotics can only be obtained by a doctor’s prescription in the UK, but it is relatively commonplace in many low- and middle-income countries for the drugs to be bought over the counter.

The report published on Friday urges governments, regulators and online firms to clamp down on unlicensed sales of antibiotics.

It comes amid global alarm about the discovery in China of a gene that makes bacteria resistant to even the strongest available antibiotic, prompting some scientists to warn the world is on the cusp of a ‘post-antibiotic era.’

In the government-commissioned report, former Goldman Sachs chief economist Jim O’Neill said the global threat is exacerbated by patients self-medicating with drugs from online pharmacies.

“Even in those countries where it’s next to impossible to buy antibiotics over-the-counter in a shop, it’s still often the case that an unscrupulous online pharmacy is just a few clicks away,” he said in a statement.

“These internet drug stores could be based anywhere in the world, so it’s vital that regulators – along with the industry, customs organizations and internet companies – work together to crack down.”

O’Neill said over-the-counter sales of antibiotics “remains relatively commonplace in Southern and Eastern Europe and many low- and middle-income countries.”

Overmedication and misuse of antibiotics is a major contributor to the evolution of bacteria resistance.

It is thought the overuse of colistin – the drug of last resort – in farm animals led to the creation of the world’s first completely antibiotic-resistant bacteria which was discovered in China.

The new mutation, dubbed the MCR-1 gene, may have already spread to Laos and Malaysia.

Professor Timothy Walsh of the University of Cardiff’s Institute of Infection & Immunity told the BBC the world is on the cusp of the “post-antibiotic era.”

“All the key players are now in place to make the post-antibiotic world a reality,” he said.

“If MCR-1 becomes global, which is a case of when not if, and the gene aligns itself with other antibiotic resistance genes, which is inevitable, then we will have very likely reached the start of the post-antibiotic era.

“At that point if a patient is seriously ill, say with E. coli, then there is virtually nothing you can do,” he added.

[buywell3] 04/12/2015 22:20

There are many small companies with computer modeled offerings to big Pharma within ADME Tox and some more in the Genetic area.


Cyprotex are accelerating their Computer modeled offerings BUT are doing so to satisfy clients wants.

They also are doing so to meet what the FDA , EMA and EPA mandate thus not offering something which looks good but is not mandated or what big Pharma wants.

Money is therefore not wasted and clients wishes are met and hopefully orders follow.

I expect to see more in-silico offerings to swell and compliment the growth of the BioSciences division ... in this way bigger pharma companies within the personalized medicine area will start to use Cyprotex , Companies that have not done so before.

Plus the IP that Cyprotex possesses grows.

[rrb] 04/12/2015 07:51

A competitor?



Software eases pain of drug discovery

By Jane Bird (FT)


Scientists at Inventiva, a drug-discovery company, used to spend long hours collecting data manually from the machines that run their experiments so they could be analysed. Now, the business, based in the French city of Dijon, has deployed software that allows all its devices to talk to each other and share data across the business.

The technology gives the company a lead in the complex process of drug discovery, says Philippe Masson, head of screening and compound management at Inventiva, which is developing treatments for cancer and fibrosis. The new software “is significantly boosting the speed of identifying new compounds. It has made analysing the data 10 times faster”.

The previous process of copying and pasting data between systems was time-consuming and error-prone, says Mr Masson. “And the way in which data were presented made efficient analysis very difficult.” With drugs costing an average of $1.8bn to develop, anything that can accelerate matters and improve accuracy is hugely beneficial.

Despite advances in technology and understanding of biological systems, pharmaceuticals and biotech companies are often constrained by lack of capacity in process by the vast quantities of data generated from expensive research programmes. This is to the cost of both the company and potential patients who miss out on therapies.

Drug discovery laboratories have a longstanding need to integrate data from multiple disparate sources with different formats and much of which is high volume and complex, says Simon Kew, technology expert at PA Consulting.

“The data can range from the genomic profile of a patient to a simple measurement such as a drug’s solubility. Not many in the industry have fully integrated all their data on to one information management system,” Mr Kew says.

Inventiva’s 80 researchers work on internal programmes and in partnership with pharmaceutical companies including Chicago-based AbbVie. Their activities cover the entire drug development process, from “target validation”, identifying the particular protein or enzyme against which a drug should work, to selection of compounds for clinical trials.

The company has a library of 240,000 chemical compounds that it tests for their effectiveness against the target once it has been identified, a process known as high throughput screening (HTS).

Philippe Masson, head of screening and compound management at Inventiva

Compounds from this screening process are tested in cells for efficacy. The aim is to reduce the potential for side-effects and increase potency and metabolic stability by looking at how the drug might be absorbed, distributed in the body and excreted. This involves taking pictures of the cells as they grow and analysing them, a process known as “high content screening” (HCS).

“HTS and HCS create huge quantities of data,” says Mr Masson. “We wanted a system that lets us quickly and securely analyse the results and display images speedily alongside the numbers.”

In early 2014, Inventiva began using a software package called ActivityBase from IDBS, a company located in Guildford, UK. The two companies have worked closely to deploy the software and create an integrated system to analyse data, including images of cell development, and store them securely.

“It is a very complex system,” Mr Masson says. “Although we bought off-the-shelf software, we had to customise it.” Results can now be seen in a more accessible form on screen, for example in graphs and curves.

“It’s particularly useful to have a more graphic visualisation of our data,” he adds. “This helps us evaluate the response at different [levels of] concentration and see whether a compound is highly active or not. Our researchers can now do more experiments, analyse more compounds and take decisions more quickly.”

The software also puts Inventiva in a much stronger position competitively because it speeds up internal processes and facilitates sharing data with clients. “Even if they are using different software, we can export data as Excel or text files, which makes communicating with other systems straightforward,R21; says Mr Masson.

Inventiva is now in discussions with IDBS about how the scope of the software could be extended, for example to improve the way the experimental control data are analysed.

[buywell2] 02/12/2015 02:00

AstraZeneca caused a storm last year when Pfizer attempted a takeover – the pharma-giant's motivation? Computer-aided modelling of drugs.

We now live in a 'Big Data' world and computational modelling of biological data, or computational biology, is seeing new approaches, developments and revelations in the way we discover, deliver and understand the effect of drugs. Although Pfizer has withdrawn its takeover bid for AstraZeneca, the progress that it has made in its cancer immunotherapy research using computational biology was one of the key reasons that Pfizer was interested. It's also a very big part of why AstraZeneca was able to resist the takeover bid.

Computational biology has come on in leaps and bounds in the past few years as supercomputing and biomedical data have combined to great effect to improve our understanding of a range of things from how the body will react to drugs to why natural substances such as green tea are good for us, and also to reveal the links between certain genes and diseases.
Relating and constraining digital cell behaviour

There are two main approaches currently used in computational biology: relational databases and constraint-based models. Dr Nick Plant, reader in molecular toxicology at the University of Surrey, recently presented workshops looking at the theory behind them and how they work in practice at the 9th Annual ADMET 2014 conference, which is a major event in the pharma-industry calendar for those involved in drug discovery.

Dr Plant explained that relational databases do exactly what the name implies: they are used to relate bits of information to each other. "In a biological context, this may be as simple as the interaction of two proteins, or a more complex behaviour such as the general biological response to a chemical exposure."

So, in layman's terms, relational databases are basically our repositories of knowledge. Dr Plant compared their use to that of a dictionary, whereas the constraint-based models build upon the knowledge contained in the relational databases to turn them into 'living' computer models that can replicate biology. "They are called constraint-based as they are constrained by this knowledge, such that they can only simulate things that we have said can happen, and cannot undertake actions that we have forbidden."

This means that researchers use the dictionary contained in the relational database to generate a working model of the cells in our bodies, aiming to reproduce in a computer what we see in real life. Dr Plant says: "The reason for doing this is that in making these constraint-based models we can see new properties emerge; an analogy is that a dictionary is a set of definitions, but a very boring read – put the words together in the correct order, however, and you have a best-selling novel."
Telling biological stories

The creation of these best-selling biological novels is revealing some incredible links between genetic reactions and has also just revealed that the number of genes in the human genome is fewer than we previously thought, and means we have less than an earthworm. Dr Plant explained that as to how super-computing works in terms of biology, perhaps the greatest example of emergent behaviour is life itself. "Looking at our DNA, which can be viewed as the body's blueprint, I cannot predict what a living cell will look like, but using information from a relational database, I can constrain a model in such a way that it really does come to life in the computer and begins to look and behave just like a real cell."

What constraint-based models really do is enable us to begin to understand how different behaviours emerge from the blueprint of our DNA, so-called genotype-phenotype relationships. At Surrey University the research that Dr Plant and his colleagues are involved in is advancing our understanding of two of the biggest health problems we face in the UK.

"We have two great medical challenges: obesity-related illness and cancer," says Dr Plant. "We are still unsure how these diseases emerge from normal physiology, why some people are more susceptible than others, and how best to treat each person's disease, which is also known as personalised medicine. At Surrey, we are building models of the changes that occur within the liver during chronic over-feeding. This will, we hope, help to explain the mechanisms by which obesity leads to disease such as metabolic syndrome, diabetes and liver failure, and how to prevent and treat this."
Genetic revelations through personalised models

In a related project, Dr Plant's team have also looked at data on the genetic make-up from 2,000 breast cancer patients to build personalised models of their tumours. This has allowed them to identify the characteristics that lead to aggressive tumours with a poor patient survival rate. "We are using these characteristics to develop biomarkers that help us to identify these individuals. Then we can develop treatments specifically aimed to be most effective in this currently poorly responsive group of patients."

At present, constraint-based models are largely restricted to simulations of single cells and the short- to medium-term goal of the computational biology community is to create joined up models that allow more complex parts of biology, such as whole organs or tissues, to be modelled. Dr Plant said that there are already exciting advances being made towards this goal: "Using software developed at Surrey, we are currently making such multi-scale models of the liver that truly live and breathe, as they are able to respond to changes in the environment. As we incorporate more features in these models they become more accurate and can reproduce more of the abilities of complex organs such as the liver."

In the long-term, it's hoped that they will be able to join all of these models together to create true digital organisms that are faithful representations of all the complexities of life within a computer. "Such advances will allow us to better predict how the body will respond to, for example, changes in its environment or the development of disease. This will allow us to target our experimental work more effectively, with the twin aim of bringing safe, efficacious drugs to market sooner, and reducing the number of animal experiments that are required, as we will have digital rats, mice, dogs, etc, as well as a digital human."

As well as the revelation that the human genome has fewer genes, and the exciting developments in obesity and cancer research at Surrey University, there has been a flurry of research discovery announcements in the computational biology world this year.
Alzheimer's and brain cancer

At the Houston Methodist Research Institute (HMRI), a team led by Dr Stephen Wong, the founding chairman of HMRI's Department of Systems Medicine and Bioengineering, has revealed a link between Alzheimer's, the most prevalent form of neurodegenerative disease, and glioblastoma multiform (GBM), which is the most aggressive form of brain cancer.

Using supercomputers at the Texas Advanced Computing Center (TACC) at The University of Texas at Austin, the team analysed and compared data from thousands of genes in order to narrow the search for the common cell signalling pathways of these two diseases. What it revealed is that they share a pathway in gene transcription, a process essential for cell reproduction and growth. What it means for treatment research is now that the pathway has been identified, the information can be used to design a new therapeutic strategy that targets that pathway.
Green tea's role in lowering cholesterol

The health benefits of drinking green tea have long been recognised and it has been a major component of Chinese medicine for centuries. However, research scientists at Sun Yat-Sen University in China have now used computational biology modelling to reveal how green tea metabolites act on human enzymes to lower blood cholesterol levels.

With 2012 statistics showing that six in ten adults in the UK have raised blood cholesterol levels, and the 2004 INTERHEART global case-control study (one of the largest and most important cardiology studies ever conducted) estimating that 45 per cent of heart attacks in Western Europe are due to abnormal blood lipids, this is an exciting discovery that is expected to lead to a real breakthrough in prevention and treatment of cardiovascular disease.

Dr Jose M Prieto-Garcia, lecturer in Pharmacognosy at the Centre for Pharmacognosy and Phytotherapy at University College London (UCL), said that the potential impact of this discovery is that the pharma-industry could now use these products as lead compounds to develop more potent synthetic ones and provide new medicines for the treatment of cholesterolemia, which plays a major role in the development of cardiovascular disease.

"Catechins inhibit many enzymes in vitro, so could potentially exert a positive influence in the metabolism of mammals," says Dr Prieto-Garcia.

These catechins are found in many fruits and vegetables, known as superfoods for their role in keeping our bodies fit and healthy, as well as in widely consumed leafy plants such as tea. Green tea is one of the most accessible and richest sources of catechins, but other important sources are dark chocolate, cherries and red wine.

Prior to this recent discovery, Dr Prieto-Garcia said that because catechins can polymerise into tannins, which precipitate with proteins and lead to the 'dry mouth feel' (astringent effect) of tea or some red wines, many research scientists questioned the in vitro effects of catechins and thought that they were a consequence of unspecific precipitation rather than specific interactions.

The research team in China tested the activity of three enzymes, which are essential for cholesterol biosynthesis in vitro, in the presence of four different polyphenols that are found in green tea. They found that two of the polyphenols could inhibit all three enzymes simultaneously, whereas the other two polyphenols had no effect whatsoever. The team then used computational modelling techniques to work out how the inhibiting polyphenols bind to the enzymes to prevent their function.

Dr Prieto-Garcia says: "Essentially, what this research demonstrates is that catechins can – in theory – interact with the active sites of three enzymes that are essential for cholesterol biosynthesis. So, potentially, a regular intake of catechins will result in a decreased de novo synthesis of cholesterol and help to lower levels of it in the blood."
Computational biology at UCL

The development of computational biology techniques is also benefitting the research that Dr Prieto-Garcia is doing at UCL. This is currently focused in three key areas: herb/drug interactions, the use of natural products against cancer migration and the prediction of bioactivities of complex natural products by artificial intelligence.

"In the past, we could only make relationships between a few parameters and the pharmacological effect. With these modern computational methods we can now make relationships with all the data we have and the observed effect, so we can effectively pinpoint which parameters are more relevant, thus speeding up research."

His research involves looking for functional compounds from plant extracts containing dozens of components, which could be added in small amounts to improve the efficacy of existing drugs and/or herbal remedies to improve performance. It is also focused on discovering the synergies and antagonisms between functional compounds and computational biology is moving research into all three areas forwards. "By applying computational methods we can infer which subset of natural compounds is linked to the pharmacological effect, which allow us to isolate the bioactive fraction faster."

But speeding up the rate of discovery and isolation of these compounds is not the only benefit that computation biology is bringing to Dr Prieto-Garcia's research: "On the other side we can model how the natural molecules actually work on our body.'By doing this we can propose the mechanisms that should be used to get the effects we want, then validate our proposals. All of which is resulting in a better understanding of the therapeutic potential of these natural products."

So what are the healthcare benefits that patients can expect to see from these research advances? They include faster development and approval of new drug treatments. "It helps speed up the 'bench to bedside' process. Namely, more natural promising molecules can be fed into the drug pipeline and eventually one could become a medicine," Dr Prieto-Garcia explains.

However, there is enormous potential for these technologies to help people in advance of needing drug treatments and also for the health benefits of natural compounds to be available much faster than drugs that have to go through years of testing and approvals processes. "When formulations of natural products from plants that are already present in the diet show promising functional properties, they can quickly be provided to the public in the form of food supplements (or 'nutraceuticals')," says Dr Prieto-Garcia. "They may help the population to slow down the onset of some conditions associated with the normal ageing process."
Long-term achievements

The advances that computational biology is bringing to research at UCL, and other universities and pharma companies, is playing a vital role in moving towards achieving the long-term goal of healthcare researchers the world over: to prevent rather than cure diseases.

Dr Prieto-Garcia concludes: "This is especially important in chronic disorders associated with ageing. In my research at UCL, computational biology is helping us to pinpoint more and more the naturally occurring products in our food, which, properly enriched and formulated, may help to delay or mitigate the deleterious effects of such conditions. Once the disease is present, medicines inspired in such natural molecules could provide us with the enhanced pharmacological effect to treat them."
Mental health advances

So as the physical health problems we face and how to treat them are becoming better understood, supercomputing is now being adopted for 'computational psychiatry' to try and make the same level of advances in our understanding of mental health disorders.

The world's first computational psychiatry centre opened in London in April 2014 and it has been funded by a five-year £4.1m investment from the Max Planck Society and UCL. Researchers there will use powerful modern technology to create more detailed models than ever before of how the human brain works.

These models will then be linked to measurements of behaviour and changes in brain function to help identify the causes of a range of common mental health problems so that personalised treatments can be developed.

The Centre will be based between UCL (University College London) and the Max Planck Institute for Human Development in Berlin and led by Professor Ray Dolan FRS, director at the UCL Wellcome Trust Centre for Neuroimaging and Professor Ulman Lindenberger, director at the Max Planck Institute for Human Development.

It's expected that the discoveries made there will spearhead new perspectives on psychiatric disorders that will realise major benefits for patients within a decade.

So if you combine the advances of sculpting drugs to treat physical ailments with those to treat psychiatric ones, and being able to tailor them to individual patients' needs, then it seems that the future for human healthcare that's been created by supercomputing is truly revolutionary.

[buywell2] 02/12/2015 01:44

I have posted many times on this and other threads regarding the importance of a company like Cyprotex owning its own Intellectual Property (IP).


This differentiates Cyprotex from other Contract Research Organizations (CRO's ) that just provide service/s to the likes of BIG Pharma.


The value that will probably get placed upon the IP that Cyprotex owns when a takeover occurs a few years hence ... will in my estimation be over 50% of the price paid.

Thus it is good to read the recent RNS's whereby Cyprotex are creating computer based models that predict a variety of ADME Tox and Genetic outcomes regarding the testing of new drug compounds.

Amalgamating some of these new models with the likes of Cyprotex IP owned Cloe PK , expands and enhances Cloe ... (which itself has attracted interest from BIG Pharma in the past), and brings it forwards into new areas of interest and development by the FDA and hence BIG Pharma.

I hope to read that when Cyprotex make their next acquisition ... it also will bring some unique IP with it which Cyprotex can build upon and hence add further value to the takeover pot.



The founder of Cyprotex in 1999 was DE Leahy .... he still hold Cyprotex shares ... the drive to reduce the use of animals has grown exponentially since


Abstract

Send to:
Expert Opin Drug Metab Toxicol. 2006 Aug;2(4):619-28.

Integrating in vitro ADMET data through generic physiologically based pharmacokinetic models.
Leahy DE Author information

Abstract

Early estimation of kinetics in man currently relies on extrapolation from experimental data generated in animals.

Recent results from the application of a generic physiologically based model, Cloe PK) (Cyprotex), which is parameterised for human and rat physiology, to the estimation of plasma pharmacokinetics, are summarised in this paper.

A comparison with predictive methods that involve scaling from in vivo animal data can also be made from recently published data. On average, the divergence of the predicted plasma concentrations from the observed data was 0.47 log units. For the external test set, > 70% of the predicted values of the AUC were within threefold of the observed values. Furthermore, the model was found to match or exceed the performance of three published interspecies scaling methods for estimating clearance, all of which showed a distinct bias towards overprediction. It is concluded that Cloe PK, as a means of integrating readily determined in vitro and/or in silico data, is a powerful, cost-effective tool for estimating exposure and kinetics in drug discovery and risk assessment that should, if widely adopted, lead to major reductions in the need for animal experimentation.

[buywell3] 29/11/2015 22:26

Worth a read

[buywell3] 29/11/2015 22:12

Development/s on the Household Products front



Nov 3rd 2015


UK bans animal testing of household products

Campaign groups want ingredients covered and prohibition extended across Europe


A UK ban on animal testing of household products came into force on 1 October.

The ban covers detergents, air fresheners, paints and varnishes but biocides, food contact materials and cosmetics are excluded. It also only covers finished products and not individual ingredients.

People for the Ethical Treatment of Animals (Peta UK) welcomed the move – promised by the government earlier this year (CW 23 March 2015) – as a “step in the right direction”. But science policy adviser, Julia Baines, said that animal testing on finished household products has not happened in Britain since 2010 and the ban should be extended to their ingredients.

“There are already an abundance of household products and ingredients on the market, and there can be absolutely no circumstances under which we can justify poisoning and killing animals to develop more products,” she said.

The European Coalition to End Animal Experiments (ECEAE) has recently launched a campaign for such a ban to be extended across the whole of Europe (CW 14 August 2015).

The UK Home Office has also published its latest annual statistics regarding scientific procedures on living animals. This shows a 42% increase in the number from 2005 to 2013, but a 6% fall between 2013 and 2014.

In 2014, there were 3.87m completed, of which 1.94m were related to the breeding of genetically altered animals not used in further procedures. The remaining 1.93m were experimental.

[buywell3] 26/11/2015 00:23

I remain convinced that the FDA and other government agencies will have to mandate human cell based in-vitro assays to substantiate computer modelled results.

Especially as some of this data is derived from FDA mandated acute toxicity animal testing.

The LD50 (lethal dose 50%) is a common used baseline required by BIG Pharma

Interestingly the LD used to kill the animal , is done so over a relatively short timescale
This is done on ALL pre-clinical testing of new drug compounds.


What the FDA do not specify is , as far as I have read, a longer lower dose of acute toxicity animal testing ... whereby a time is found , which might be for example a year ... before a test animal dies


The actual dose then would be MUCH lower than currently obtained

The cost of animal testing would rocket

The data would be better than that currently used which results in human organ damage over the long term eg 6 months and longer.

Humans are currently the guinea pigs which is why litigation claims run into the $BILLIONS and approved FDA drugs get withdrawn years later after approval.




From the cyprotex website



I like this ...

High Content Screening: Cell-based Assays for In Vitro Toxicology Prediction
Confocal HCS image of 3D Cardiac Microtissues

Posted 25th November 2015 by Cyprotex

High Content Screening (HCS), also known as High Content Analysis (HCA) or High Content Imaging (HCI), is a powerful tool in preclinical drug discovery. Depending on the type of analysis needed, HCS can be used to predict toxicity, confirm or identify targets or pathways for lead compounds, or even elucidate possible mechanism of action for orphan compounds.

High Content Screening uses automated microscopy to evaluate cellular responses to xenobiotics, typically by using fluorescent dyes or fluorescently labelled antibodies to mark specific phenotypic features of a cell, like proteins or organelles. Multiple dyes known to bind to specific cell sites can be employed at the same time because each has a specific light wavelength that causes them to fluoresce. This can provide a rich set of data that may show multiple mechanisms of toxicity from a single compound within individual cells.

Like standard microscopes, HCS instruments employ one of three types of light sources that cause excitation of the fluorescent dyes; lamps, lasers or light emitting diodes (LEDs), each with their own advantages and disadvantages. The excitation responses are recorded as images, and after acquisition is complete, the images gathered are analysed by specialised software programmed to quantify phenotypic differences in a given cell type. It is often within the software provided that the greatest differences in HCS platforms are evident. Despite the fact that the instruments themselves vary in many ways, such as light source, environmental control capabilities and objective type, they serve the same purpose: to aggregate images. The ability to accurately analyse these images lies in the software. Building analysis algorithms and statistical models should occur during assay development whenever possible. As a cell-based assay is validated, phenotypic response can and should be used to define criteria for analysis, thus reducing false positives and false negatives, so the ability to customise and extend a platform to fit the goals of an HCS program is critical.

Phenotypic screening on HCS platforms can provide a wealth of cellular response information. Depending on the objectives, these data can be used to assess biological responses and identify potential therapeutic targets, or suggest possible mechanistic pathways.

Cyprotex have recently authored a publication entitled ‘High-Content Screening : Understanding and Managing Mechanistic Data to Better Predict Toxicity’. The book chapter by Walker et al., (2015) was published in Computational Systems Toxicology (Editors, Hoeng J and Peitsch M). The chapter covers HCS approaches used to determine drug-induced cellular toxicity.

[buywell3] 25/11/2015 22:22

SBS need to get into food DNA and bacterial testing for the Supermarkets and Government agencies first.



Cyprotex are doing the right thing at the moment and their computer models will be used increasingly by other industries.

Their expansion of DNA testing services/assays will I hope gain some breadth and traction into 2016.

[p1nkfish] 21/11/2015 00:41

Source Biosciences analytical testing side combined with CRX (merger or acquisition) could make a powerful UK combo.

I had wondered ifvthere might be some sniffing arounf CRX recently.

Results will be improved over last half but the perkiness in the price might be more than that.

[buywell3] 19/11/2015 22:57

buywell2 has mentioned 30M several times in recent years

Another decent contract win might do the trick ... perhaps a government one ?



Is Cyprotex plc a Buy? The Stock Gapped Up Today
November 16, 2015 ·

The stock of Cyprotex plc (LON:CRX) gapped up by GBX 0.747 today and has GBX 229.38 target or 176.00% above today’s GBX 83.11 share price. The 6 months technical chart setup indicates low risk for the GBX 18.39 million company. The gap was reported on Nov, 17 by Barchart.com. If the GBX 229.38 price target is reached, the company will be worth GBX 32.37M more.

Gaps up are useful for using as a support level and to some extent as a tradeable event. If investors already hold the stock and experience a price gap up, then its usually a good idea to hold the stock for a stronger up move. Back-tests of these patterns indicate that two-thirds of the times the stock performance improves after the gap. The area gaps close 89% of the time, the breakaway gaps, 2%, the continuation gaps 4% and the exhaustion gaps 61%. The stock increased 3.89% or GBX 3.11 on November 16, hitting GBX 83.11. About 72,681 shares traded hands or 320.41% up from the average. Cyprotex plc (LON:CRX) has risen 50.00% since April 20, 2015 and is uptrending. It has outperformed by 53.47% the S&P500.










After Today’s Huge Increase, Is Cyprotex plc’s Near-Term Analysis Positive?
November 17, 2015

The stock of Cyprotex plc (LON:CRX) is a huge mover today! The stock is down 1.06% or GBX 0.89 after the news, hitting GBX 83.11 per share. Cyprotex plc (LON:CRX) has risen 50.00% since April 20, 2015 and is uptrending. It has outperformed by 52.54% the S&P500.

The move comes after 9 months positive chart setup for the GBX 17.97M company. It was reported on Nov, 17 by Barchart.com. We have GBX 159.57 PT which if reached, will make LON:CRX worth GBX 16.53M more.

[buywell3] 19/11/2015 22:35

Re my last post also read


Whilst 2012 ... it contains some decent thoughts/facts

also

EPA Science Matters Newsletter: EPA's ToxCast and ExpoCast: Chemical Screening, Better and Faster (Published January 2014)

EPA scientists and partners are advancing the next generation of chemical safety assessments.
Scientist pouring liquid into Erlenmeyer flask

As demand for chemical safety information increases, there is a need to develop safety assessment tools that can be applied to large numbers of chemicals. Traditional testing methods rely on the use of laboratory animals and are slow and costly. Typically, scientists expose small rodents or fish to the substance they are testing and then carefully observe the animal for signs of disease or other harmful effects.

Thoroughly testing even a single substance can take years, and costs can run into the millions of dollars.

With the relatively slow pace of testing and with hundreds of new chemicals introduced into the marketplace every year, it's easy to see the enormous challenge facing EPA policy makers and others working to advance the safe and sustainable production, use, and disposal of chemicals.

To make testing faster and more efficient, EPA scientists are harnessing advances in exposure science, molecular and systems biology, chemistry, toxicology, mathematics, and computer technology. In doing this, they are helping to revolutionize chemical screening and evaluating techniques.

A major part of this effort is the Agency's Toxicity Forecaster, or "ToxCast." ToxCast uses automated, robotic-assisted "high-throughput screening assays" to expose living cells to chemicals. The cells are then screened for biological activity and other changes that might suggest potential toxic effects. These innovative methods have the potential to limit the number of necessary laboratory animal-based toxicity tests while quickly and efficiently screening large numbers of chemicals and other substances.
Tox21

ToxCast is part of EPA's contribution to a federal research collaboration called Toxicity Testing in the 21st Century, or "Tox21," which pools resources and expertise from EPA partners from the National Institutes of Health and the U.S. Food and Drug Administration to use robotics to screen tens of thousands of chemicals for potential toxicity.

Toxicity Testing in the 21st Century

Toxicity Forecaster (ToxCast™)

How much faster and less costly could such an innovative approach be? Thoroughly testing even a single substance can take years and costs can run into the millions of dollars. In the initial phase of the ToxCast effort, EPA researchers and their partners collated the results from 30 years and $2 billion worth of traditional toxicity testing to evaluate how these new methods may more selectively target which tests are performed on which chemicals – thereby potentially saving millions of dollars and animal lives.

“ToxCast gives us a snapshot of how thousands of chemicals may perturb important biological processes leading to potential toxicity. This knowledge helps us to prioritize chemicals for more in depth evaluation.” says Dr. Russell Thomas, director of EPA's National Center for Computational Toxicology.

National Center for Computational Toxicology (NCCT)

Results of Phase I, concluded in 2010, have been widely published in peer-reviewed literature (see Update on EPA's ToxCast Program: Providing High Throughput Decision Support Tools for Chemical Risk Management), and all data sets are publicly available for online independent analysis through the ToxCast database. This research shows ToxCast can help profile and prioritize chemicals to help predict toxicity.

Update on EPA's ToxCast program: providing high throughput decision support tools for chemical risk management.

In addition, scientists have published papers in scientific journals using ToxCast data that correlate perturbation of certain cellular processes with specific toxic responses.

In 2013, EPA researchers have now moved into the second phase of ToxCast. This phase used the new, automated methods to evaluate over 2,000 chemicals from a broad range of sources, including industrial and consumer products, food additives, and potentially "green" substances that could replace existing chemicals. Screening includes assays to test for different types of toxicity such as reproductive and developmental effects, and cancer.

[redprince] 19/11/2015 21:54

Surely if the loan note debt had been bought it would require an RNS?

I am very sceptical that this has actually happened in fact would go as far as to say it has not.

[buywell3] 19/11/2015 21:39

Cyprotex initiative is ''on the money''

Here is what the EPA have to say


''Toxicity Testing in the 21st Century

Toxicity Forecaster (ToxCast™)

How much faster and less costly could such an innovative approach be? Thoroughly testing even a single substance can take years and costs can run into the millions of dollars. In the initial phase of the ToxCast effort, EPA researchers and their partners collated the results from 30 years and $2 billion worth of traditional toxicity testing to evaluate how these new methods may more selectively target which tests are performed on which chemicals – thereby potentially saving millions of dollars and animal lives.

“ToxCast gives us a snapshot of how thousands of chemicals may perturb important biological processes leading to potential toxicity. This knowledge helps us to prioritize chemicals for more in depth evaluation.” says Dr. Russell Thomas, director of EPA's National Center for Computational Toxicology.''






Also ...


The FDA is keen on predictive modelling re toxicity issues


Likewise the Environmental Protection Agency(EPA) in the USA , that Cyprotex have been/are carrying out work for in relation to their ToXcast program, are also keen on predictive modelling solutions and have awarded contracts to companies that have such.

Cyprotex are on to something with their recent in-silico RNS's

The FDA at present mandate one rodent and one non rodent species for pre-clinical acute toxicology testing.

Thus Cyprotex using the rat model looks a good initial call.

Perhaps they will include a non rodent at some point depending on uptake and requests on animal type.


The cost of using live animals is BIG

I have read some years back that it cost the EPA over 1 Billion dollars to test several hundred chemical compounds for their early stage ToxCast initiative.

They have around 10,000 chemical compounds to test.

The FDA sees in-silico predictive modelling as a quick,easy and modern day solution to many of their ADME Tox problems.

However its applications also lie in many other industries such as the tobacco , cosmetics, food, drink, chemical and household industries to name but a few.

The FDA will however be VERY unwise to just mandate Predictive computer based testing to replace animals in pre-clinical testing.

Results of such tests need to be double checked using human living 'cell based' assays that substantiate the in-silico results .

Cyprotex are getting themselves involved now in actual clinical(human) issues with their use of clinical data results ... which is a first

Previously Cyprotex has been involved in pre-clinical issue/work

Read the last annual report for other info

[p1nkfish] 19/11/2015 19:07

I bought into the loan notes and have had no information relating to any changes to them, changes realted to their issuance etc.

[husbod] 19/11/2015 15:57

A few small holders taking profits. Maybe that's what the buyer wanted or maybe not.

[market sniper1] 19/11/2015 15:30

Lovely move up here. Loads err money.

[rrb] 19/11/2015 15:13

Agreed. Buywell's input and informative posts always appreciated. I hope he is right on the loan notes. If he is, the mcap is less than 2 x revenues for a global leader in a market that is set to enjoy multiple double-digit growth for many years to come.

[husbod] 19/11/2015 14:52

Greetings rrb. Buywell is good at posting info but not so good at responding to questions.

His silence could of course reflect an inability to give the details rather than discourtesy.

Anyway, someone is buying whatever shares seem to be available and the rest of us are sitting on our stash watching.

I wish I had L2 to see the volume of shares available as small buys are pushing up the price on a regular basis.

[rrb] 19/11/2015 13:52

I'm still here Husbod!! Watching but with caution. Recall the last time we were here - spike to 14p and the 50% reversal. If the loan notes overhang has cleared, then this thing will explode to the upside. I too am eagerly awaiting buywell's response...