Regenerative orthopaedics: in vitro, in vivo...in silico

Identifying the patient harms to include in an in silico clinical trial

BACKGROUND AND OBJECTIVE

Clinical trials represent a crucial step in the development and approval of medical devices. These trials involve evaluating the safety and efficacy of the device in a controlled setting with human subjects. However, traditional clinical trials can be expensive, time-consuming, and ethically challenging. Augmenting clinical trials with data from computer simulations, so called in silico clinical trials (ISCT), has the potential to address these challenges while satisfying regulatory requirements. However, determination of the patient harms in scope of an ISCT is necessary to ensure all harms are sufficiently addressed while maximizing the utility of the ISCT. This topic is currently lacking guidance. The objective of this work is to propose a general method to determine which patient harms should be included in an ISCT for a regulatory submission.

METHODS

The proposed method considers the risk associated with the harm, the impact of the device on the likelihood of occurrence of the harm and the technical feasibility of evaluating the harm via ISCT. Consideration of the risk associated with the harm provides maximum clinical impact of the ISCT, in terms of focusing on those failure modes which are most relevant to the patient population. Consideration of the impact of the device on a particular harm, and the technical feasibility of modeling a particular harm supports that the technical effort is devoted to a problem that (1) is relevant to the device in question, and (2) can be solved with contemporary modeling techniques.

RESULTS AND CONCLUSIONS

As a case study, the proposed method is applied to a total shoulder replacement humeral system. With this framework, it is hoped that a consistent approach to scoping an ISCT can be adopted, supporting investment in ISCT by the industry, enabling consistent review of the ISCT approach across device disciplines by regulators, and providing maximum impact of modeling technologies in support of devices to improve patient outcomes.

Biological properties of terpinolene evidenced by in silico, in vitro and in vivo studies: A systematic review

BACKGROUND

Terpinolene, a monoterpene that is naturally found in a variety of herbs, is widely used as a flavoring agent in the industry. Although it's well established in the literature that terpinolene is an important component of plant extracts, the biological properties and the potential therapeutic use of this compound remain poorly explored.

PURPOSE

This work aimed to answer the following guiding question: "What are the biological activities of terpinolene demonstrated through in silico, in vitro, and in vivo assays?".

STUDY DESIGN AND METHODOLOGY

A systematic review was carried out in four electronic databases (Embase, Web of Science, Scopus, and PubMed) according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, using the following search terms: terpinolene "AND" activity "OR" properties "OR" therapeutic "OR" treatment. This search included manuscripts published between 1960 and June 2020. Study selection was conducted by two independent reviewers according to predefined criteria.

RESULTS

The initial search found a total of 2449 articles. However, only 57 of them were selected as they met the inclusion criteria and answered the guiding question. The analysis of these studies indicated that terpinolene presents a series of biological effects, from which the antioxidant, larvicide, and insecticide activities stand out. Despite the evidence demonstrating that terpinolene has the potential to be used in a broad pharmacological context, the mechanisms underlying its cellular and molecular effects remain to be better elucidated. In addition, the in vivo efficacy and safety of the administration of this compound have been poorly evaluated through either preclinical and clinical trials. Therefore, this study highlights the importance of characterizing the biological aspects and mechanisms of action of this natural compound.

CONCLUSION

The data summarized in the present systematic review demonstrates the pharmacological potential of terpinolene. Nevertheless, most studies included in this review provide a superficial characterization of terpinolene biological effects and therefore, further research elucidating its mechanism of action and potential therapeutic benefits through preclinical and clinical trials are required. Nevertheless, due to its wide range of different biological activities, terpinolene will certainly attract the interest of scientific research, which could significantly contribute to the development of new products with both therapeutic and environmental applications.

Scientific and regulatory evaluation of mechanistic in silico drug and disease models in drug development: Building model credibility

The value of in silico methods in drug development and evaluation has been demonstrated repeatedly and convincingly. While their benefits are now unanimously recognized, international standards for their evaluation, accepted by all stakeholders involved, are still to be established. In this white paper, we propose a risk‐informed evaluation framework for mechanistic model credibility evaluation. To properly frame the proposed verification and validation activities, concepts such as context of use, regulatory impact and risk‐based analysis are discussed. To ensure common understanding between all stakeholders, an overview is provided of relevant in silico terminology used throughout this paper. To illustrate the feasibility of the proposed approach, we have applied it to three real case examples in the context of drug development, using a credibility matrix currently being tested as a quick‐start tool by regulators. Altogether, this white paper provides a practical approach to model evaluation, applicable in both scientific and regulatory evaluation contexts.

In Silico Clinical Trials in the Orthopedic Device Industry: From Fantasy to Reality?

The orthopedic device industry relies heavily on clinical evaluation to confirm the safety, performance, and clinical benefits of its implants. Limited sample size often prevents these studies from capturing the full spectrum of patient variability and real-life implant use. The device industry is accustomed to simulating benchtop tests with numerical methods and recent developments now enable virtual "in silico clinical trials" (ISCT). In this article, we describe how the advancement of computer modeling has naturally led to ISCT; outline the potential benefits of ISCT to patients, healthcare systems, manufacturers, and regulators; and identify how hurdles associated with ISCT may be overcome. In particular, we highlight a process for defining the relevant patient risks to address with ISCT, the utility of a versatile software pipeline, the necessity to ensure model credibility, and the goal of limiting regulatory uncertainty. By complementing-not replacing-traditional clinical trials with computational evidence, ISCT provides a viable technical and regulatory strategy for characterizing the full spectrum of patients, clinical conditions, and configurations that are embodied in contemporary orthopedic implant systems.

Blackboard to Bedside: A Mathematical Modeling Bottom-Up Approach Toward Personalized Cancer Treatments

Cancers present with high variability across patients and tumors; thus, cancer care, in terms of disease prevention, detection, and control, can highly benefit from a personalized approach. For a comprehensive personalized oncology practice, this personalization should ideally consider data gathered from various information levels, which range from the macroscale population level down to the microscale tumor level, without omission of the central patient level. Appropriate data mined from each of these levels can significantly contribute in devising personalized treatment plans tailored to the individual patient and tumor. Mathematical models of solid tumors, combined with patient-specific tumor profiles, present a unique opportunity to personalize cancer treatments after detection using a bottom-up approach. Here, we discuss how information harvested from mathematical models and from corresponding in silico experiments can be implemented in preclinical and clinical applications. To conceptually illustrate the power of these models, one such model is presented, and various pertinent tumor and treatment scenarios are demonstrated in silico. The presented model, specifically a multiscale, hybrid cellular automaton, has been fully validated in vitro using multiple cell-line-specific data. We discuss various insights provided by this model and other models like it and their role in designing predictive tools that are both patient, and tumor specific. After refinement and parametrization with appropriate data, such in silico tools have the potential to be used in a clinical setting to aid in treatment protocols and decision making.

Computational Modeling and Reverse Engineering to Reveal Dominant Regulatory Interactions Controlling Osteochondral Differentiation: Potential for Regenerative Medicine

The specialization of cartilage cells, or chondrogenic differentiation, is an intricate and meticulously regulated process that plays a vital role in both bone formation and cartilage regeneration. Understanding the molecular regulation of this process might help to identify key regulatory factors that can serve as potential therapeutic targets, or that might improve the development of qualitative and robust skeletal tissue engineering approaches. However, each gene involved in this process is influenced by a myriad of feedback mechanisms that keep its expression in a desirable range, making the prediction of what will happen if one of these genes defaults or is targeted with drugs, challenging. Computer modeling provides a tool to simulate this intricate interplay from a network perspective. This paper aims to give an overview of the current methodologies employed to analyze cell differentiation in the context of skeletal tissue engineering in general and osteochondral differentiation in particular. In network modeling, a network can either be derived from mechanisms and pathways that have been reported in the literature (knowledge-based approach) or it can be inferred directly from the data (data-driven approach). Combinatory approaches allow further optimization of the network. Once a network is established, several modeling technologies are available to interpret dynamically the relationships that have been put forward in the network graph (implication of the activation or inhibition of certain pathways on the evolution of the system over time) and to simulate the possible outcomes of the established network such as a given cell state. This review provides for each of the aforementioned steps (building, optimizing, and modeling the network) a brief theoretical perspective, followed by a concise overview of published works, focusing solely on applications related to cell fate decisions, cartilage differentiation and growth plate biology. Particular attention is paid to an in-house developed example of gene regulatory network modeling of growth plate chondrocyte differentiation as all the aforementioned steps can be illustrated. In summary, this paper discusses and explores a series of tools that form a first step toward a rigorous and systems-level modeling of osteochondral differentiation in the context of regenerative medicine.

Orthopaedic regenerative tissue engineering en route to the holy grail: disequilibrium between the demand and the supply in the operating room

Orthopaedic disorders are very frequent, globally found and often partially unresolved despite the substantial advances in science and medicine. Their surgical intervention is multifarious and the most favourable treatment is chosen by the orthopaedic surgeon on a case-by-case basis depending on a number of factors related with the patient and the lesion. Numerous regenerative tissue engineering strategies have been developed and studied extensively in laboratory through in vitro experiments and preclinical in vivo trials with various established animal models, while a small proportion of them reached the operating room. However, based on the available literature, the current strategies have not yet achieved to fully solve the clinical problems. Thus, the gold standards, if existing, remain unchanged in the clinics, notwithstanding the known limitations and drawbacks. Herein, the involvement of regenerative tissue engineering in the clinical orthopaedics is reviewed. The current challenges are indicated and discussed in order to describe the current disequilibrium between the needs and solutions made available in the operating room. Regenerative tissue engineering is a very dynamic field that has a high growth rate and a great openness and ability to incorporate new technologies with passion to edge towards the Holy Grail that is functional tissue regeneration. Thus, the future of clinical solutions making use of regenerative tissue engineering principles for the management of orthopaedic disorders is firmly supported by the clinical need.

Process System Engineering Methodologies Applied to Tissue Development and Regenerative Medicine

Tissue engineering and the manufacturing of regenerative medicine products demand strict control over the production process and product quality monitoring. In this chapter, the application of process systems engineering (PSE) approaches in the production of cell-based products has been discussed. Mechanistic, empirical, continuum and discrete models are compared and their use in describing cellular phenomena is reviewed. In addition, model-based optimization strategies employed in the field of tissue engineering and regenerative medicine are discussed. An introduction to process control theory is given and the main applications of classical and advanced methods in cellular production processes are described. Finally, new nondestructive and noninvasive monitoring techniques have been reviewed, focusing on large-scale manufacturing systems for cell-based constructs and therapeutic products. The application of the PSE methodologies presented here offers a promising alternative to overcome the main challenges in manufacturing engineered tissue and regeneration products.

How Not To Drown in Data: A Guide for Biomaterial Engineers

High-throughput assays that produce hundreds of measurements per sample are powerful tools for quantifying cell-material interactions. With advances in automation and miniaturization in material fabrication, hundreds of biomaterial samples can be rapidly produced, which can then be characterized using these assays. However, the resulting deluge of data can be overwhelming. To the rescue are computational methods that are well suited to these problems. Machine learning techniques provide a vast array of tools to make predictions about cell-material interactions and to find patterns in cellular responses. Computational simulations allow researchers to pose and test hypotheses and perform experiments in silico. This review describes approaches from these two domains that can be brought to bear on the problem of analyzing biomaterial screening data.

The Holy Grail of Orthopedic Surgery: Mesenchymal Stem Cells-Their Current Uses and Potential Applications

Only select tissues and organs are able to spontaneously regenerate after disease or trauma, and this regenerative capacity diminishes over time. Human stem cell research explores therapeutic regenerative approaches to treat various conditions. Mesenchymal stem cells (MSCs) are derived from adult stem cells; they are multipotent and exert anti-inflammatory and immunomodulatory effects. They can differentiate into multiple cell types of the mesenchyme, for example, endothelial cells, osteoblasts, chondrocytes, fibroblasts, tenocytes, vascular smooth muscle cells, and sarcomere muscular cells. MSCs are easily obtained and can be cultivated and expanded in vitro; thus, they represent a promising and encouraging treatment approach in orthopedic surgery. Here, we review the application of MSCs to various orthopedic conditions, namely, orthopedic trauma; muscle injury; articular cartilage defects and osteoarthritis; meniscal injuries; bone disease; nerve, tendon, and ligament injuries; spinal cord injuries; intervertebral disc problems; pediatrics; and rotator cuff repair. The use of MSCs in orthopedics may transition the practice in the field from predominately surgical replacement and reconstruction to bioregeneration and prevention. However, additional research is necessary to explore the safety and effectiveness of MSC treatment in orthopedics, as well as applications in other medical specialties.

In silico regenerative medicine: how computational tools allow regulatory and financial challenges to be addressed in a volatile market

The cell therapy market is a highly volatile one, due to the use of disruptive technologies, the current economic situation and the small size of the market. In such a market, companies as well as academic research institutes are in need of tools to advance their understanding and, at the same time, reduce their R&D costs, increase product quality and productivity, and reduce the time to market. An additional difficulty is the regulatory path that needs to be followed, which is challenging in the case of cell-based therapeutic products and should rely on the implementation of quality by design (QbD) principles. In silico modelling is a tool that allows the above-mentioned challenges to be addressed in the field of regenerative medicine. This review discusses such in silico models and focuses more specifically on the bioprocess. Three (clusters of) examples related to this subject are discussed. The first example comes from the pharmaceutical engineering field where QbD principles and their implementation through the use of in silico models are both a regulatory and economic necessity. The second example is related to the production of red blood cells. The described in silico model is mainly used to investigate the manufacturing process of the cell-therapeutic product, and pays special attention to the economic viability of the process. Finally, we describe the set-up of a model capturing essential events in the development of a tissue-engineered combination product in the context of bone tissue engineering. For each of the examples, a short introduction to some economic aspects is given, followed by a description of the in silico tool or tools that have been developed to allow the implementation of QbD principles and optimal design.

Early BMP, Wnt and Ca(2+)/PKC pathway activation predicts the bone forming capacity of periosteal cells in combination with calcium phosphates

The development of osteoinductive calcium phosphate- (CaP) based biomaterials has, and continues to be, a major focus in the field of bone tissue engineering. However, limited insight into the spatiotemporal activation of signalling pathways has hampered the optimisation of in vivo bone formation and subsequent clinical translation. To gain further knowledge regarding the early molecular events governing bone tissue formation, we combined human periosteum derived progenitor cells with three types of clinically used CaP-scaffolds, to obtain constructs with a distinct range of bone forming capacity in vivo. Protein phosphorylation together with gene expression for key ligands and target genes were investigated 24 hours after cell seeding in vitro, and 3 and 12 days post ectopic implantation in nude mice. A computational modelling approach was used to deduce critical factors for bone formation 8 weeks post implantation. The combined Ca(2+)-mediated activation of BMP-, Wnt- and PKC signalling pathways 3 days post implantation were able to discriminate the bone forming from the non-bone forming constructs. Subsequently, a mathematical model able to predict in vivo bone formation with 96% accuracy was developed. This study illustrates the importance of defining and understanding CaP-activated signalling pathways that are required and sufficient for in vivo bone formation. Furthermore, we demonstrate the reliability of mathematical modelling as a tool to analyse and deduce key factors within an empirical data set and highlight its relevance to the translation of regenerative medicine strategies.

Capturing the wide variety of impaired fracture healing phenotypes in Neurofibromatosis Type 1 with eight key factors: a computational study

Congenital pseudarthrosis of the tibia (CPT) is a rare disease which normally presents itself during early childhood by anterolateral bowing of the tibia and spontaneous tibial fractures. Although the exact etiology of CPT is highly debated, 40–80% of CPT patients are carriers of a mutation in the Neurofibromatosis Type 1 (NF1) gene, which can potentially result in an altered phenotype of the skeletal cells and impaired bone healing. In this study we use a computational model of bone regeneration to examine the effect of the Nf1 mutation on bone fracture healing by altering the parameter values of eight key factors which describe the aberrant cellular behaviour of Nf1 haploinsufficient and Nf1 bi-allelically inactivated cells. We show that the computational model is able to predict the formation of a hamartoma as well as a wide variety of CPT phenotypes through different combinations of altered parameter values. A sensitivity analysis by “Design of Experiments” identified the impaired endochondral ossification process and increased infiltration of fibroblastic cells as key contributors to the degree of severity of CPT. Hence, the computational model results have added credibility to the experimental hypothesis of a genetic cause (i.e. Nf1 mutation) for CPT.

Computational modeling of bone fracture non-unions: four clinically relevant case studies

The human skeleton has a remarkable regeneration capacity. Nevertheless, 5-10 % of the bone fractures fails to heal and develops into a non-union which is a challenging orthopedic complication requiring complex and expensive treatment. This review paper will discuss four different computational models, each capturing a particular clinical case of non-union: non-union induced by reaming of the marrow canal and periosteal stripping, non-union due to a large interfragmentary gap, non-union due to a genetic disorder [i.e. NF1 related congenital pseudoarthrosis of the tibia (CPT)] and non-union due to mechanical overload. Together, the four computational models are able to capture the etiology of a wide range of fracture non-union types and design novel treatment strategies thereof. Further research is required to corroborate the computational models in both animal and human settings and translate them from bench to bed side.

The role of growth factors in stem cell-directed chondrogenesis: a real hope for damaged cartilage regeneration

PURPOSE

The use of stem cells in regenerative medicine offers hope to treat numerous orthopaedic disorders, including articular cartilage defects. Although much research has been carried out on chondrogenesis, this complicated process is still not well understood and much more research is needed. The present review provides an overview of the stages of chondrogenesis and describes the effects of various growth factors, which act during the multiple steps involved in stem cell-directed differentiation towards chondrocytes.

METHODS

The current literature on stem cell-directed chondrogenesis, in particular the role of members of the transforming growth factor-β (TGF-β) superfamily-TGF-βs, bone morphogenetic proteins (BMPs) and fibroblast growth factors (FGFs)-is reviewed and discussed.

RESULTS

Numerous studies have reported the chondrogenic potential of both adult- and embryonic-like stem cells and the role of growth factors in programming differentiation of these cells towards chondrocytes. Mesenchymal stem cells (MSCs) are adult multipotent stem cells, whereas induced pluripotent stem cells (iPSC) are reprogrammed pluripotent cells. Although better understanding of the processes involved in the development of cartilage tissues is necessary, both cell types may be of value in the clinical treatment of cartilage injuries or osteoarthritic cartilage lesions.

CONCLUSIONS

MSCs and iPSCs both present unique characteristics. However, at present, it is still unclear which cell type is most suitable in the treatment of cartilage injuries.