Information

What are some good examples of open-source articles in which the synergy of two medicines is demonstrated?

What are some good examples of open-source articles in which the synergy of two medicines is demonstrated?


We are searching data for your request:

Forums and discussions:
Manuals and reference books:
Data from registers:
Wait the end of the search in all databases.
Upon completion, a link will appear to access the found materials.

I am doing research on Stochastic Cooperative Game Theory (a subfield in mathematics), which I will henceforth call SCGT for convenience. In this theory, entities can work together to receive a bigger combined payoff than they would otherwise receive if they had not worked together. In the stochastic version of cooperative game theory, the payoffs are not deterministic, but follow a probability distribution.

It seemed to me I could apply this theory to drug synergy. If there is drug synergy, there is a (high) chance that two medicines combined are better at healing a patient than just multiplying the dosage of either medicine by $2$. With SCGT, I could determine how much each medicine contributes to the healing of the patient, if some information is known about the drug-response curves. This in turn could tell us something about how much the manufacturers of each drug receive to be paid (in theory).

However, I am not quite well-acquainted with the literature on drug synergy. Furthermore, I can't access many articles on the topic without paying a lot (as I'm with the mathematics department at the university, I can't view articles on biology for free).

So my questions are:

  1. Do you know any open-source articles in which it is shown that two drugs work in synergy according to the Bliss Independence model?

and:

  1. Do you know any open-source articles in which it is shown that three or more drugs work in synergy according to the Bliss Independence model?

The same questions apply to the Loewe additivity framework.


Rethinking embryology in vitro: A synergy between engineering, data science and theory

Synthetic embryology provides a previously inaccessible window to early development.

Engineering methods allow to control in vitro systems at will to explore new concepts.

Data science (imaging and -omics) allows identification of underlying patterns.

Theory and mathematical modeling are vital to make predictions and test hypotheses.

Combination of these techniques will push synthetic embryos towards new horizons.


Taming the Body’s ‘Microbial Wolves’

The session kicked off with a talk from Dr. Ted Fjällman, CEO of London-based Prokarium, which hijacks an attenuated strain of Salmonella enterica as a delivery vector for oral vaccines and for microbial immunotherapy applications.

Fjällman began with a simple question: “How can we tame [microbes] and…expose them to the right environment so that we can get ‘microbial wolves’ to work for us?”

While research has historically focused on microbes that cause harm and how to stop them, Prokarium instead enlists these so-called ‘microbial wolves’ of the body, like S. enterica (some strains of which cause Typhoid fever or food poisoning), to fight against disease. Attenuated strains of S. enterica have already demonstrated efficacy as oral vaccine delivery systems in numerous clinical trials, but Prokarium wants to take this strain to the next level.

Fjällman highlighted Prokarium’s development of an engineered S. enterica that functions as an oral vaccine delivery system against Yersinia pestis, the plague-causing bacterium, which has proven effective in preclinical trials. The company will take this engineered strain to the clinic this year, together with the UK’s Defence Science and Technology Laboratory.

But Fjällman announced further plans to harness the potential of this once-dangerous microorganism, elaborating on the capabilities of S. enterica as a tool to release cancer-seeking payloads that modulate tumor microenvironments.

“[Salmonella] is able to get into a tumor and…bring a payload or cargo that can modulate the tumor microenvironment,” said Fjällman. Prokarium believes that attenuated S. enterica, which is advantageous relative to other delivery vectors because of its large size, could also work synergistically with other therapies, making it a powerful contender for state-of-the-art immuno-oncology applications.

The Vaxonella® platform.


Building the chain of translatability

Disease understanding. Knowledge at the molecular level of the causes and drivers of the disease is a crucial success factor for PDD, as it is needed to select and to validate the best experimental cellular system and readouts to use (Fig. 1). Experience has shown that assays with generic readouts (for example, viability or apoptosis of cancer cell lines) are often not causally related to the disease biology pathways that we are attempting to modify, and thus are less likely to be useful in identifying novel and efficacious molecular MoAs.

a | The first step in establishing a chain of translatability for phenotypic drug discovery (PDD) is identifying a disease-associated molecular characteristic or signature (for example, a disease-associated gene expression profile, as shown, or the presence of a particular mutation in a protein) that differentiates the disease state (right) from normal physiology (left). When available human genetic or genomic data are insufficient to establish the causal components of this signature, animal models of the same disease can reconstruct earlier biological processes and associated pathway changes, providing a mechanistic bridge between alterations to normal physiology and the manifestations of the disease. b | Having identified the disease characteristics, cellular models aim to reconstruct a cellular phenotype that is as close as possible to the disease condition for example, by incorporating a specific mutation in the cells or deriving cells from patients via induced pluripotent stem (iPS) cell generation. Specific disease-relevant stimuli may be required to model the cellular phenotype that is seen in the disease state. The mechanistic similarity of the model to the clinical disease is determined by a comparison of the molecular phenotype signatures. If the signatures are not sufficiently similar, the model is considered invalid. c | Phenotypic screening is conducted using a cellular model validated by the molecular phenotype. Prioritized hits from the primary screen may reveal different molecular phenotypes corresponding to different mechanisms of action (MoAs). Only MoAs that affect disease-relevant pathways will be evaluated for in vivo proof-of-concept. Nonspecific MoAs (represented by compound 3) can be eliminated using molecular phenotype information prior to advancing to in vivo proof-of-concept evaluation.

Although there remain diseases for which the molecular-mechanistic disease understanding may be insufficient to undertake effective PDD, this is changing rapidly as, for example, next-generation sequencing is contributing growing amounts of genetic data for many disorders 23 . For some diseases, especially those that require biopsies for diagnosis or treatment follow-up, there may be a large body of genetic and genomic information related to the baseline condition and to disease progression. This is, for instance, the case in kidney diseases 24,25 , for which this systems biology information has enabled the identification of new mechanisms and targets through the integration of large-scale genetic and molecular data with deep phenotypic information. This information has already been successfully translated into the identification of novel drugs through TDD approaches, such as the JAK2 inhibitor baricitinib 26 , which has reached late-stage clinical development for rheumatoid arthritis. However, attempts to use such knowledge to develop biologically informed PDD screens for kidney diseases have not yet been successful because it has not been possible to faithfully capture the complex human kidney pathophysiology in a suitable cellular assay system. Nevertheless, we are optimistic that these challenges can be overcome with the adoption of more sophisticated emerging models, such as organ-on-a-chip 27 .

Incomplete disease understanding is a limitation for the validation of phenotypic models and for hypothesis-driven molecular targets. This is illustrated by the challenges of transgenic mouse models of Alzheimer disease, which have been widely used, but have been unsuccessful in identifying clinically effective therapeutics so far. Although the molecular driver may be the same in both animal models and humans, the resulting pathogenic mechanism does not seem to be fully recapitulated in animal models 28 . Thus, capturing human disease relevance is the first step in the creation of a chain of translatability. Therefore, when starting a PDD programme, we need to be aware of the molecular mechanistic information that is available for the disease that we want to replicate in vitro and we should ideally place that molecular information in the context of clinical data. Are the translational data sufficient to identify well-validated molecular functional end points or predictive biomarkers for disease modification that can guide the PDD effort? If the same molecular functions and readouts can be encoded in a phenotypic screening model, then predictive validity is enhanced. Two key areas that can help to translate disease information into a screen with strong predictive validity are molecular phenotyping and advanced cellular models.

Molecular phenotyping. As we mentioned above, whereas knowledge of the molecular drivers of disease has been central to TDD approaches, the potential impact has not yet been fully realized in the context of PDD. A major challenge has been the substantial inability to translate such molecular MoA findings in humans in the context of a disease-relevant cell system that is appropriate for high-throughput hit identification. Molecular phenotyping 29,30 — the ability to run high-throughput transcriptome analysis as a secondary or even a primary screen — thus holds promise as a technology to fully leverage this molecular information. Several such efforts are ongoing in the computational biology 30,31,32 , pharmaceutical 33,34 and toxicogenomics 35,36 fields. These efforts have the common aim of showing that the activity of signalling networks can be assessed based on a set of established key regulatory and effector genes. Molecular phenotype gene signatures have been shown by several groups 31,33,36 to consistently deliver an accurate pathway-centric view of the biological system under study. The modulation of signalling networks identified in this way has been shown to be consistent with literature or experimental data assessed by different technologies.

In PDD, this means that we have a powerful tool to decode the effect of compounds on regulatory pathways in the context of the cellular model adopted. Pioneering work in this respect by Drawnel, Zhang and colleagues was recently published 37 . The authors were able to show, using a 917 human pathway reporter gene signature 31 , that molecular phenotyping can cluster compounds based on pathway profiles and can simultaneously dissect associations between pathway activities and disease phenotypes. Molecular phenotyping was applicable to compounds with a range of binding specificities and allowed false positives derived from high-content screening assays to be triaged. The approach was used to identify a class of calcium-signalling modulators that reversed disease-regulated pathways and phenotypes, which was validated by structurally distinct compounds in relevant classes 37 .

A similar approach was recently used to discover leptin sensitizers for diabetes. Here, researchers used profiling information on an active compound coupled with a search of the Broad Institute connectivity map (CMAP) to identify withaferin A as a novel leptin sensitizer 38,39 . We believe that such an approach, used in synergy with molecular disease information that is being generated by multiple initiatives 40,41,42 that are sequencing DNA from patients with various diseases and phenotypically profiling them (for example, Genomics England 41 and Genome Asia 100K 43 ), may become a key enabler of future PDD. The critical value of this approach in establishing a chain of translatability is twofold. It first offers an unbiased diagnosis of the similarity between the disease state in humans and the molecular state of the discovery model (as shown in Fig. 2), and it also provides an evaluation of the extent to which a potential therapeutic modifies the molecular state towards the therapeutically desired state.

a | The disease model and the disease are represented as hidden state-dependent networks, and assay end points reflect the model state. On the left-hand side, a disease model that depends on a non-physiological external stimulus is shown, for which the assay end points are driven by network nodes that have no overlap with the disease state. Consequently, the assay end points are poorly predictive of a therapeutic effect. In the centre, the assay system state shares some common pathways with the disease, and the effects on some, but not all, of the assay end points may be predictive of a therapeutic effect. On the right-hand side, the network of the assay model strongly overlaps with the disease, and the effects on assay end points are highly predictive of a therapeutic effect. b | Illustration of how increasing the complexity of the assay model, from 2D cell culture (left) to a 3D culture (centre) and to a 3D co-culture system (right) might increase the overlap between the causal networks for the assay and disease end points, as well as the probability that a given assay readout will be predictive.

Advanced cellular models. The cellular screening system is a cornerstone of most successful attempts to identify potential novel drugs. Now, technological advances in cell and molecular biology are enabling the development of models that are likely to strengthen the chain of translatability even in model systems that have a reduced physiological complexity, by more closely modelling the disease-relevant cell or cells and tissue, and/or by focusing on the molecular and mechanistic phenotype.

In recent years, a broad arsenal of advanced cellular models 44,45 have become available as microtechnologies have progressed: microprinted tumour spheroids 46,47 , 'tissue-on-a-chip' (Ref. 27), structured co-cultures and multicellular organoids 48,49,50,51,52 . Each system has its strengths and weaknesses reviewed in the references provided. Complementary advances in screening hardware, high-throughput cell assay technologies such as confocal high-content imaging systems and other methods for monitoring cell function are enabling more complex assays to be implemented for high-throughput lead discovery.

In addition to models that address the anatomical complexities of in vivo tissue structures, PDD efforts can leverage the predictive potential of iPS cell-based models 53,54 , which promise to replicate a disease in a dish (comprehensively reviewed by Avior et al. 54 ). Models using iPS cells are especially powerful when studying high-penetrance monogenic disorders that are associated with a clear cellular phenotype. Breakthroughs in gene-editing technologies such as CRISPR–Cas are also likely to greatly increase the number and the diversity of genetically defined cellular models 4,5 , both conventional and iPS derived, used for PDD in the near future. At an even higher degree of complexity, an iPS cell-based model can be coupled to a molecular readout such as endogenous gene expression. For example, a screen carried out by Lee et al. 55 assessed the ability of more than 6,000 molecules to restore the expression of IKK complex-associated protein (IKBAP), evaluated by real-time quantitative reverse-transcriptase PCR in cells derived from patients suffering from familial dysautonomia, who carry a hypomorphic mutation in the IKBAP gene. Nevertheless, even in the most advanced areas to make use of iPS-derived cell models — cardiac and neurological disorders — most studies have so far been aimed at validating the effects of existing drugs in a repurposing effort (see Table 3 in Avior et al. 54 ) rather than identifying starting points for new drugs, reflecting the relatively short period for which iPS phenotypic screens have been pursued.

To address recurring concerns regarding the maturation state of iPS-derived cells, the use of patient-derived primary cells is a possible alternative. Sourcing such cells is still a rate-limiting step, but it is an area in which public–private partnerships and collaborations between biotech and pharma companies and disease foundations, as well as direct collaborations with health centres, hold great promise 56 . The translational value of these systems has been exemplified in the development of ivacaftor by scientists at Vertex Pharmceuticals 57 , including its label expansion based on an additional clinical trial of patients selected based on their genotype following compound testing against a wide range of genotypes encoded in patient-derived primary cells 58 . Fully differentiated patient-derived primary bronchial epithelial cells from healthy individuals or patients with cystic fibrosis harbouring the CFTR Δ508 mutation have also recently been used by scientists at Pfizer in a PDD project for cystic fibrosis 59 .

In the cancer drug discovery arena, results in the past few years from Cancer Genome Atlas data have highlighted the disconnections between even the best-characterized cancer cell line models and patients 60,61,62 . Concurrently, technical advances in generating patient-derived tumour models in vivo and in vitro are having radical effects on cancer drug research that ought to have a favourable impact on phenotypic discovery models. Two of the best-established patient-derived cancer cell culture systems are probably the glioma-derived neurosphere model and colorectal cancer-derived organoids. Both of these models, like the tumours from which they are derived, have a clear stem cell component that makes them amenable to genome editing 63 and scalable for high-throughput screening 64,65 . The genetic diversity of tumours is thus not only captured but can also be made available through biobanks (for example, see Ref. 66).

However, powerful mechanistically informed cellular models do not always demand the use of a complex cellular system — the most important factor is that the molecular mechanism of the disease is reproduced in the observed phenotype of the discovery model (Fig. 2). In a striking example of a 'rule of 3 breaker', investigators from Roche and Novartis independently discovered small molecules that correct aberrant alternate splicing of the mRNA that codes for survival motor neuron 1 (SMN1), which is the root cause of the rare neurodegenerative disease, spinal muscular atrophy (SMA). Importantly, both molecules were optimized without prior knowledge of their molecular target by screening using generic cell lines that expressed reporter gene constructs designed to detect the alternative splicing of SMN1 (Refs 29,67). This was achieved despite a widely held consensus that reporter gene assays in engineered cell systems have low disease relevance and have arguably led to only a single marketed drug (vismodegib) 6 , presumably due to the smaller biological space that they probe (that is, direct transcriptional regulation) and high technical false-positive rates 68 . The cellular system in both cases was very simple but the proximity to the disease phenotype (that is, the ability to assess aberrant alternative splicing of a single gene) unparalleled. This resulted in an assay that was capable of guiding structure–activity relationship (SAR) studies, as well as producing molecules shown to be effective in disease models 29,67 , which are currently in late-stage clinical development for SMA.

Recent antibiotic discovery efforts have also provided instructive examples of the application of novel readout technologies to a simple 'classical' assay system to drive the exploration of new regions of chemical space. As discussed above, simple assays based on killing bacteria in vitro have a strong alignment to the desired pharmacodynamic effect in animal models and so are likely to identify hits that can be optimized into leads that show in vivo efficacy. The hurdle faced by antibiotic developers is that such chemical hits are frequently rediscoveries of known chemical scaffolds and thus are not appropriate for the development of drugs in novel classes, which are highly desirable in order to overcome resistance to antibiotics in existing classes. The challenge of identifying novel chemical starting points can be addressed by using discovery models that directly focus on a molecular phenotype. Two recent studies have illustrated this concept. Both groups took the approach of characterizing signatures predictive of the MoA of available antibiotics, and searched for novel hits that had a similar mechanistic profile but with an insufficient potency to be found in a classical functional antibacterial screen. Nonejuie et al. 69 adopted high-content screening (HCS) to measure a large number of cellular features, whereas a second group at Roche extended this idea to the molecular level by using RNA-seq to identify drug-specific gene expression signatures (Zoffmann, S. et al., unpublished observations presented at the 2016 Keystone symposium 'Modern Phenotypic Drug Discovery: Defining the Path Forward'). Both approaches indicated the ability to identify cellular pathways that predicted the MoAs of known antibacterial molecules. The team at Roche was able to further translate the results from RNA-seq to a higher-throughput bacteria reporter strain-based signature, and also reported that the signature allowed the identification of novel hits with the desired molecular MoA, thus providing novel chemical starting points.

To summarize, we believe that the ability to capture a disease-relevant molecular MoA in the screening system is a key enabling feature of PDD. Disease relevance can potentially be encoded in a simple cellular system, and novel chemical space may be explored by adopting innovative readouts for which a chain of translatability has been established. In the absence of the three core elements mentioned above — disease knowledge, replication and/or monitoring of the molecular MoA in vitro, and availability of a suitable cellular system 8 — the probability of a successful PDD programme is greatly reduced.


Introduction

Preclinical development for drugs in neglected diseases remains a slow process due to a lack of access to compounds, and legal complications over intellectual property ownership. One way to accelerate drug discovery is to provide open access to bioactive molecules with public disclosure of the resulting biological data. The data from open access of bioactive molecules can help prioritize which compounds to investigate further through medicinal chemistry for the original indication and can also uncover other indications for compound development. It was in this spirit of providing open access of malaria-bioactive compounds, and disseminating the results in the public domain, that the Malaria Box project was initiated by the Medicines for Malaria Venture.

Origins of the ‘Malaria Box’ compound set

Since 2007, over 6 million compounds were screened against asexual-stage Plasmodium falciparum, at two pharmaceutical companies (GlaxoSmithKline [1] and Novartis [2]), and two academic centers (St. Jude, Memphis [3], and Eskitis, Australia [4]), resulting in over 20,000 compounds active in the low- to sub-micromolar range. The structures of the 20,000 anti-malaria hits were made available in ChEMBL (www.ebi.ac.uk/chembl), but discussions with biology groups had underlined the importance of access to the compounds themselves for testing. Cluster analysis and commercial availability reduced this to a set of 400 representative compounds, the ‘Malaria Box’, which was distributed freely to researchers who provided a rationale for screening [5]. This paper presents a summary and analysis of the collected results of the Malaria Box screening from 55 groups who performed a wide variety of assays, the large majority of which are presented in this paper. The collective results are greater than the sum of the individual assays, because each compound can be queried for activity, pharmacokinetic, and safety data to gauge its suitability as a starting point for subsequent medicinal chemistry optimization efforts.


Selected possibilities for phytocannabinoid-terpenoid synergy

Cannabis and acne

AEA simulates lipid production in human sebocytes of sebaceous glands at low concentrations, but induces apoptosis at higher levels, suggesting that this system is under ECS control ( Dobrosi et al., 2008 ). CBD 10–20 µM did not affect basal lipid synthesis in SZ95 sebocytes, but did block such stimulation by AEA and arachidonate ( Biro et al., 2009 ). Higher doses of CBD (30–50 µM) induced sebocyte apoptosis, which was augmented in the presence of AEA. The effect of CBD to increase Ca ++ was blocked by ruthenium red, a TRP-inhibitor. RNA-mediated silencing of TRPV1 and TRPV3 failed to attenuate CBD effects, but experiments did support the aetiological role of TRPV4, a putative regulator of systemic osmotic pressure (T. Bíró, 2010, pers. comm.). Given the observed ability of CBD to be absorbed transcutaneously, it offers great promise to attenuate the increased sebum production at the pathological root of acne.

Cannabis terpenoids could offer complementary activity. Two citrus EOs primarily composed of limonene inhibited Propionibacterium acnes, the key pathogen in acne (MIC 0.31 µL·mL −1 ), more potently than triclosan ( Kim et al., 2008 ). Linalool alone demonstrated an MIC of 0.625 µL·mL −1 . Both EOs inhibited P. acnes-induced TNF-α production, suggesting an adjunctive anti-inflammatory effect. In a similar manner, pinene was the most potent component of a tea-tree eucalyptus EO in suppression of P. acnes and Staph spp. in another report ( Raman et al., 1995 ).

Considering the known minimal toxicities of CBD and these terpenoids and the above findings, new acne therapies utilizing whole CBD-predominant extracts, via multi-targeting ( Wagner and Ulrich-Merzenich, 2009 ), may present a novel and promising therapeutic approach that poses minimal risks in comparison to isotretinoin.

MRSA accounted for 10% of cases of septicaemia and 18 650 deaths in the USA in 2005, a number greater than that attributable to human immunodeficiency virus/acquired immunodeficiency syndrome ( Bancroft, 2007 ). Pure CBD and CBG powerfully inhibit MRSA (MIC 0.5–2 µg·mL −1 ) ( Appendino et al., 2008 ).

Amongst terpenoids, pinene was a major component of Sideritis erythrantha EO that was as effective against MRSA and other antibiotic-resistant bacterial strains as vancomycin and other agents ( Kose et al., 2010 ). A Salvia rosifolia EO with 34.8% pinene was also effective against MRSA (MIC 125 µg·mL −1 ). The ability of monoterpenoids to enhance skin permeability and entry of other drugs may further enhance antibiotic benefits ( Wagner and Ulrich-Merzenich, 2009 ).

Given that CBG can be produced in selected cannabis chemotypes ( de Meijer and Hammond, 2005 de Meijer et al., 2009a ), with no residual THC as a possible drug abuse liability risk, a whole plant extract of a CBG-chemotype also expressing pinene would seem to offer an excellent, safe new antiseptic agent.


What Is the Result?

According to an article published in Cell, the patterns that the neural network can detect in the structure of antibacterial substances are enough to spot potential antimicrobial agents among different compounds. Particularly, among compounds that were predicted by neural networks and scientists to have antibacterial action, more than half turned out to actually be working antibiotics.

Scientists were able to find at least one potent substance, the antibacterial properties of which had not previously been known. This was a compound that scientists called "halicin" — an understudied kinase inhibitor, previously not used as an antibiotic. A number of laboratory experiments were conducted with it, and scientists discovered that this substance is really able to inhibit the growth of a wide range of bacteria, including those strains that are resistant to most modern antibiotics. This happened due to the following mechanism (previously not used in antibiotics): halicin inhibits the proton pump activity by reducing the sensitivity of bacteria membranes to changes in pH. And since a proton pump is the most important component of the bacterial cell, it is incompatible with its vital functions.

In addition to halicin, the neural network predicted at least eight new compounds that could have antibacterial properties. In these compounds, it also found mechanisms that had never been used as antibacterial agents before and at least two of them showed successful results during laboratory research. The scientists note that although these results look impressive, there are still many difficulties to be encountered in further studies of this type.


The Mevalonate Pathway and Terpenes: a Diversity of Chemopreventatives

The goal of the present review is to give an overview of the most recent papers demonstrating the chemoprevention effects of terpenes. We were interested in showing the structural diversity of these compounds and elucidating overlapping mechanistic factors that may be responsible for chemoprevention by the terpenes in general in these effects.

Recent Findings

The studies reviewed point to chemoprevention effects across the broad array of structural classes of the terpenes, from the very small-molecule monoterpenes (10 carbon atoms) to the tetraterpenes (40 carbon atoms). These compounds have chemopreventative effects in cancers of the colon, bladder, skin, and liver. Some studies demonstrated that natural product mixtures have more robust effects and that synergy between compounds can be found in these natural products.

Summary

Terpenes are the most diverse class of compounds on earth. The complex biology of animals including the development of cancers has evolved with these compounds enabling numerous structurally diverse groups of the terpenes to have similar effects on the development and progression of cancers. Mechanistically, these actions tend to cluster into effects of reactive oxygen species and mediators of inflammation which are key players in carcinogenesis.


Toxicity

Owing to their mechanism of action, IO agents are associated with a unique but variable spectrum of toxicities, known as irAEs [84], [85]
. While the toxicities can vary greatly depending on the patient, the risk of serious clinical problems developing limits the use of IO agents to specialist clinicians with the experience to deal with irAEs should they arise. The most serious concern is potential supra-physiologic stimulation of the immune system leading to a potentially life-threatening uncontrolled and rapid production of pro-inflammatory cytokines (a so-called &lsquocytokine storm&rsquo)
[85] . Since there are several potential irAEs that can present following initiation of IO therapy, it is important to have clear and robust guidelines of when to refer to other medical specialists who are able to provide input to managing individual patients. For this to work in practice, it is essential that good relationships are developed with other specialties, perhaps most importantly gastroenterology, endocrinology and dermatology. The European Society for Medical Oncology (ESMO) clinical practice guidelines, &lsquoManagement of toxicities from immunotherapy&rsquo, contain comprehensive guidance for the use of IOs in the clinic (see Figure 2).


Figure 2: The most common immune-related adverse events associated with the use of immune checkpoint inhibitors

Abx: Antibiotics CRP: C-reactive protein G: grade irAE: immune-related adverse event

For the ICPis, the frequency of irAEs with anti-PD-1/PD-L1 agents appears to be lower than that for anti-CTLA-4 therapies, with the most frequently observed irAEs being mild fatigue, rash, pruritis and gastrointestinal disturbances. The occurrence of grade 3 or grade 4 toxicities with CTLA-4 inhibitors appears to be 20&ndash30% compared with 10&ndash15% for anti-PD-1/L1 agents, with the most serious being dysimmune colitis and interstitial pneumonitis. Delayed hepatic, gastrointestinal and endocrine toxicities can also occur with IO agents and, as with ipilimumab, might only present after the final dose has been administered (see Figure 5) [86]
. Therefore, patient follow-ups are of paramount importance and, for ipilimumab, liver function tests are required prior to each dose, with elevated levels of liver enzymes or bilirubin usually prompting withholdment of treatment.

Combination treatment using two IO agents (i.e. nivolumab and ipilimumab) is currently approved for advanced melanoma, colorectal and kidney cancer [87]
, [88]
, [89]
. In one study, administration of anti-PD-1 and anti-CTLA-4 agents in combination resulted in 95% of patients experiencing irAEs, 55% of which were grade 3 or higher [90]
. Higher toxicity rates are also observed when combining conventional chemotherapy with anti-CTLA-4 agents, such as ipilimumab (58%) compared with chemotherapy alone (42%) [90]
.

A meta-analysis, published in 2017, has revealed that ICPi therapy is associated with a risk of death from a variety of irAEs [91]
. Although this study concluded that clinical specialists should be aware of these potentially serious complications, in reality, the risk of fatal irAEs is low and should not prevent the use of IO agents that can be potentially curative for some patients. For example, in one study, 3,545 patients treated with ICPis were reviewed and the rate of fatal irAEs found to be 0.59% (i.e. seven cases with ipilimumab, nine with anti-PD-1 agents and five with a combination) [92]
. In another study, a meta-analysis of ICPi trials involving 19,217 patients demonstrated that the overall toxicity rate ranged from 0.36% to 1.23%. Other researchers identified a total of 613 irAE-related fatalities from screening the World Health Organization Vigilyze pharmacovigilance database for fatal toxicity events associated with ICPis [92]
. They concluded that fatal irAEs may not have been recorded as consistently as for conventional AEs, but instead noted as &lsquocomplications&rsquo of irAEs (e.g. sepsis following colon perforation) [92]
.

The results of clinical trials with combinations of ICPis have revealed an increased incidence of irAEs, and the occurrence of grade 3 or grade 4 toxicities is significantly higher with IO combination therapies compared with monotherapy [93]
. There is currently only one ICPi combination approved for clinical use &mdash nivolumab and ipilimumab &mdash for the treatment of metastatic melanoma and previously untreated advanced RCC [94]
. While the concept of IO combination therapies is still in its infancy, in the first six months of 2017, 403 combination trials were underway, a dramatic increase from 2013 when only 20 combination clinical trials were active [95]
.

As a general rule, where irAEs of any grade present in a patient, the initial management is to monitor, which is often quickly followed by withholding treatment and commencing corticosteroids. GI toxicity is the most frequently reported irAE of any grade associated with anti-CTLA4 therapy and is managed with a combination of fluids and anti-diarrhoeal agents, and sometimes intravenous steroids if symptoms are severe (see Figure 4) [90]
. However, in 2018, two cancer patients who developed colitis caused by immunotherapy and failed to respond to these supportive therapies based on current guidelines, were successfully treated with faecal microbiota transplants. While this study was based on a small number of patients, it suggested the potential for this innovative approach of using faecal microbiota to reduce adverse drug reactions (ADRs) [96]
.

Predicting the efficacy and safety of immune checkpoint inhibitors based on immune-related adverse effects

A recent study, published in 2019, has shown that patients who experience irAEs during anti-PD-1 monotherapy have a higher chance of achieving an objective response compared with those who do not experience any irAEs [97]
. This provides an opportunity to predict the likely efficacy of treatment, potentially allowing more informed decisions about whether treatment should be continued in certain patients. The study involved 106 patients who were treated with either nivolumab or pembrolizumab over a two-year period the most common irAEs were thyroid dysfunction and nephritis. The ORR for the cohort was 41.5% (n=44), but these patients represented 82.5% (n=40) of those experiencing irAEs of any grade, compared with 16.6% (n=66) who did not experience any irAEs. Furthermore, patients who experienced irAEs had significantly improved PFS than those who did not (i.e. 10 months vs. 3 months) as well as an improvement in OS (i.e. 32 months vs. 22 months), although the latter was not deemed significant on multivariate analysis [97]
.

In another study, clinical benefit associated with irAEs was observed in NSCLC patients receiving anti-PD-1 therapy who were shown to have autoimmune antibodies detectable prior to treatment. Investigators concluded that these autoimmune markers may help to determine the risk&ndashbenefit ratio for individual patients, allowing therapeutic benefit to be maximised while minimising irAEs [98]
. Based on analysis of patient records, 48% of the 137 patients were identified as having experienced irAEs, and for those whose blood samples testing positive for autoimmune factors (i.e. rheumatoid factor, antinuclear or antithyroid antibodies), significantly higher ORRs (i.e. 41% vs. 18%) and disease control rates (i.e. 81% vs. 54%) were achieved compared with those who had tested negative. PFS was also significantly improved by median values of 6.5 months versus 3.5 months. This effect appeared to be driven primarily by patients testing positive for rheumatoid factor compared with those who tested negative, with PFS values of 10.1 months and 3.7 months, respectively [98]
. A related study, published in 2019, found that patients with pre-existing antibodies were significantly more likely to experience any-grade irAEs with rates of occurrence of 60% compared with 32% in patients who tested negatively for autoimmune antibodies [99]
.

A more recent study in glioblastoma demonstrated a relationship between specific genetic alterations and immune expression signatures, and a tumour&rsquos clonal evolution during treatment with anti-PD-1 therapy [100]
. For example, certain non-response mutations have been identified in the PTEN gene, while some response-linked alterations have been identified in components of the MAP kinase pathway. This is a significant finding for glioblastoma therapy because PD-1 inhibitors have not provided a survival benefit for these patients to date. Initial clinical results suggest that a subgroup of patients may benefit from anti-PD-1 treatment (e.g. median survival in responders with ICPi therapy was 14 months vs. 10 months in non-responders).

The results of a prospective study published in early 2020 have suggested that it may be possible to predict the risk of thyroid dysfunction (i.e. destructive thyroiditis and hypothyroidism) in patients undergoing PD-1 inhibitor therapy [101]
. The study involved baseline measurements of anti-thyroid antibodies for 209 patients with re-measurement every 6 weeks for a total of 24 weeks after initiation of therapy. Thyroid dysfunction occurred in 34.1% of the 44 patients testing positive for anti-thyroid antibodies before treatment, versus 2.4% for the 165 patients testing negative at baseline. The results also support the 6&ndash7 week presentation timeline for thyroid dysfunction as indicated in Table 6, as no new cases occurred after 24 weeks post-treatment.


Table 6: Immune-related adverse advents associated with immune checkpoint inhibitors treatment (including incidence and onset of presentation)

Further research in this area may lead to methods to predict which patients are most likely to benefit from IO therapy across a wide range of tumour types.


Discussion

Previous open-access high-throughput screens have had a great impact on malaria research, and we anticipate that our data provide a rich resource in the search for new antimalarials. Despite the reliance on a nonhuman malaria species for screening, the repeated rediscovery of chemotypes with known, potent activity against P. falciparum blood stages and P. vivax liver schizonts, or clinical efficacy in humans, shows that the data from this rodent malaria model are predictive. Furthermore, liver schizonticidal activity is a required component of next-generation antimalarials proposed by Medicines for Malaria Venture, critical components of which include prophylactic and chemoprotective liver-stage efficacy after single exposure (TCP4) (30). Another advantage of the Pbluc assay is the reduced metabolic capacity of the host cells used this should result in a higher hit rate with metabolically liable compounds in a high-throughput phenotypic screen. Last, although it is possible that some compounds were missed through the use of a rodent parasite, rodent malaria remains an efficient and important in vivo model for drug efficacy testing compounds that do not act in this model would be costlier to progress into animal causal prophylaxis testing. In addition, some of the compounds that have activity here may eventually show activity against P. vivax hypnozoites, and if a radical cure chemotype is to be found, its discovery would be made much more likely through elimination of liver schizont-inactive compounds. The use of the low-cost rodent model allowed a much higher number of compounds to be evaluated than would be possible with human parasites, which can be difficult and expensive to acquire. The large size of the library used here facilitated compound clustering and allowed a probabilistic identification of active families.

The high number of parasite mitochondrial inhibitors (57) that were discovered with combined target identification methods is perhaps not surprising given that compounds were selected for target identification on the basis of potency, and substantial work has shown that mitochondrial inhibitors are very potent antimalarials. Nevertheless, the dataset contains a rich set of other ABS scaffolds that could still be good starting points for medicinal chemistry efforts designed to improve potency, selectivity, and reduced toxicity. The picomolar inhibitor and clinical candidate KAE609 was derived from an

90 nM IC50 starting point that was discovered in a high-throughput ABS screen (31).

Although our target identification efforts showed that several compounds with activity across species were mostly in known target classes, a much larger number of compounds were active in the liver stages and had no activity in the blood stages. These presumably act against host pathways that the parasite requires for development, or alternatively, the infected cell may be weakened by the presence of a parasite and be more susceptible to killing by compounds that target essential host cellular processes. It is worthwhile to mention that because there are no reported antimalarial compounds with exclusive prophylactic activity, and methods for target identification are not readily available for compounds that do not act in the blood stage, we are unable to conclude much about their mechanism of action. Nevertheless, the scaffolds should still represent important starting points for prophylaxis stage drugs and exploring new mechanism of actions.

In theory, liver-stage antimalarial compounds could function as more cost-effective “chemical vaccines” that could replace conventional vaccines in malaria-elimination campaigns, provided sufficient safety. A fully protective conventional vaccine has never been developed for malaria (32) vaccines are very species-specific (and potentially strain-specific), whereas chemotherapy is generally not, and vaccines, which typically consist of recombinant protein or a heat-killed organism, require maintenance of a cold chain. In the case of the irradiated or attenuated cryopreserved sporozoite vaccine (33), the cost of goods (sporozoites that are hand-dissected from infected mosquitoes) will be much higher than a small-molecule therapy. We estimate that it costs 10 cents per well to create the 1000 sporozoites needed for one well of a 1536-well plate. Creating enough sporozoites to immunize a human would cost many times this amount.

In an analogous situation, long-acting, injectable HIV drugs have now been developed, and their deployment may help to prevent the spread of the HIV virus (34). Such intramuscular or subcutaneous chemoprotection injections or “chemical vaccines” can be deployed in resource-poor settings, and patient compliance is not as much of an issue as with standard, orally available tablet drugs. Because the injectable typically consists of a small molecule, refrigeration and maintenance of a cold chain may not be needed. The cost of goods for an injectable that needs to be supplied once every 1 to 3 months will most likely be lower than the cumulative cost of a tablet that needs to be taken every day, even considering the cost of a syringe and a health care worker to provide delivery. There are also other low-cost delivery methods, such as patches. Thus, it seems entirely feasible that a contribution to the eradication of malaria could come through the use of a long-acting chemical vaccine.


Watch the video: What are some good examples where laziness is genius? rAskReddit (January 2023).