Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial... Show moreDevelopments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to exciting developments in the computational drug design field, facilitating biological activity prediction and de novo drug design for molecular targets of interest. Here, we describe current and future synergies between these developments to effectively identify drug candidates from the plethora of molecules produced by nature. We also discuss how to address key challenges in realizing the potential of these synergies, such as the need for high-quality datasets to train deep learning algorithms and appropriate strategies for algorithm validation. Show less
Antibody function is dependent on avidity - the accumulated strength of multiple affinity interactions between the antibody, antigen, cell surface receptors and other antibodies. In this Review,... Show moreAntibody function is dependent on avidity - the accumulated strength of multiple affinity interactions between the antibody, antigen, cell surface receptors and other antibodies. In this Review, Oostindie et al. discuss the role of avidity in eliciting antibody functional responses and review the current engineering strategies for manipulating avidity interactions in antibody-based therapies.Antibodies are the cardinal effector molecules of the immune system and are being leveraged with enormous success as biotherapeutic drugs. A key part of the adaptive immune response is the production of an epitope-diverse, polyclonal antibody mixture that is capable of neutralizing invading pathogens or disease-causing molecules through binding interference and by mediating humoral and cellular effector functions. Avidity - the accumulated binding strength derived from the affinities of multiple individual non-covalent interactions - is fundamental to virtually all aspects of antibody biology, including antibody-antigen binding, clonal selection and effector functions. The manipulation of antibody avidity has since emerged as an important design principle for enhancing or engineering novel properties in antibody biotherapeutics. In this Review, we describe the multiple levels of avidity interactions that trigger the overall efficacy and control of functional responses in both natural antibody biology and their therapeutic applications. Within this framework, we comprehensively review therapeutic antibody mechanisms of action, with particular emphasis on engineered optimizations and platforms. Overall, we describe how affinity and avidity tuning of engineered antibody formats are enabling a new wave of differentiated antibody drugs with tailored properties and novel functions, promising improved treatment options for a wide variety of diseases. Show less
Organs-on-chips (OoCs) could be useful at various stages of drug discovery and development, providing insight regarding human organ physiology in both normal and disease contexts, as well as... Show moreOrgans-on-chips (OoCs) could be useful at various stages of drug discovery and development, providing insight regarding human organ physiology in both normal and disease contexts, as well as accurately predicting developmental drug safety and efficacy. This Review discusses the advances that have enabled OoCs to demonstrate physiological relevance, and the challenges and opportunities that need to be tackled to tap the full potential of OoC utility for translational research.Organs-on-chips (OoCs), also known as microphysiological systems or 'tissue chips' (the terms are synonymous), have attracted substantial interest in recent years owing to their potential to be informative at multiple stages of the drug discovery and development process. These innovative devices could provide insights into normal human organ function and disease pathophysiology, as well as more accurately predict the safety and efficacy of investigational drugs in humans. Therefore, they are likely to become useful additions to traditional preclinical cell culture methods and in vivo animal studies in the near term, and in some cases replacements for them in the longer term. In the past decade, the OoC field has seen dramatic advances in the sophistication of biology and engineering, in the demonstration of physiological relevance and in the range of applications. These advances have also revealed new challenges and opportunities, and expertise from multiple biomedical and engineering fields will be needed to fully realize the promise of OoCs for fundamental and translational applications. This Review provides a snapshot of this fast-evolving technology, discusses current applications and caveats for their implementation, and offers suggestions for directions in the next decade. Show less
The Innovative Medicines Initiative Consortium RESOLUTE has started to develop tools and produce data sets to de-orphanize transporters in the solute carrier protein (SLC) superfamily, thereby... Show moreThe Innovative Medicines Initiative Consortium RESOLUTE has started to develop tools and produce data sets to de-orphanize transporters in the solute carrier protein (SLC) superfamily, thereby lowering the barrier for the scientific community to explore SLCs as an attractive drug target class Show less
Jonker, A.H.; Hivert, V.; Gabaldo, M.; Batista, L.; O'Connor, D.; Aartsma-Rus, A.; ... ; Ardigo, D. 2020
The International Rare Diseases Research Consortium (IRDiRC) has created a Guidebook to facilitate drug development for rare diseases by organizing available tools into a standardized framework.
Drug-induced liver injury (DILI) is a patient-specific, temporal, multifactorial pathophysiological process that cannot yet be recapitulated in a single in vitro model. Current preclinical testing... Show moreDrug-induced liver injury (DILI) is a patient-specific, temporal, multifactorial pathophysiological process that cannot yet be recapitulated in a single in vitro model. Current preclinical testing regimes for the detection of human DILI thus remain inadequate. A systematic and concerted research effort is required to address the deficiencies in current models and to present a defined approach towards the development of new or adapted model systems for DILI prediction. This Perspective defines the current status of available models and the mechanistic understanding of DILI, and proposes our vision of a roadmap for the development of predictive preclinical models of human DILI. Show less
The term bispecific antibody (bsAb) is used to describe a large family of molecules designed to recognize two different epitopes or antigens. BsAbs come in many formats, ranging from relatively... Show moreThe term bispecific antibody (bsAb) is used to describe a large family of molecules designed to recognize two different epitopes or antigens. BsAbs come in many formats, ranging from relatively small proteins, merely consisting of two linked antigen-binding fragments, to large immunoglobulin G (IgG)-like molecules with additional domains attached. An attractive bsAb feature is their potential for novel functionalities -that is, activities that do not exist in mixtures of the parental or reference antibodies. In these so-called obligate bsAbs, the physical linkage of the two binding specificities creates a dependency that can be temporal, with binding events occurring sequentially, or spatial, with binding events occurring simultaneously, such as in linking an effector to a target cell. To date, more than 20 different commercialized technology platforms are available for bsAb creation and development, 2 bsAbs are marketed and over 85 are in clinical development. Here, we review the current bsAb landscape from a mechanistic perspective, including a comprehensive overview of the pipeline. Show less
Witte, W.E.A. de; Danhof, M.; Graaf, P.H. van der; Lange, E.C.M. de 2018
